Wearable camera, wearable camera system, and information processing apparatus

ABSTRACT

A wearable camera includes a video recording device that records a captured video of a subject on the front side of a user on a recorder, a sensor that acquires information regarding motion of the user, a determiner that determines whether or not at least one default event has occurred on the basis of information regarding motion of the user acquired by the sensor during recording of the captured video of the subject, and a controller that generates event list information in which a detection time point of the default event is correlated with information regarding the default event according to determination that the at least one default event has occurred during recording of the captured video of the subject, and records the event list information on the recorder in correlation with the captured video of the subject.

BACKGROUND

1. Technical Field

The present disclosure relates to a wearable camera, a wearable camerasystem, and an information recording method, capable of generating andrecording information regarding a user's behavior in a captured video.

2. Description of the Related Art

In recent years, in order to efficiently support business of a policeofficer or a security guard, examination of an operation such as apolice officer or a security guard wearing or carrying a wearable cameraand recording captured videos on patrol has progressed.

As the related art for improving convenience of handling video datacaptured by a wearable camera, for example, a wearable camera disclosedin Japanese Patent Unexamined Publication No. 2016-122918 has beenproposed. In the wearable camera disclosed in Japanese Patent UnexaminedPublication No. 2016-122918, in a case where there is input from anattribute information assignment switch, video data captured by acapture is assigned with attribute information corresponding to settinginformation in an attribute selection switch, and is stored in astorage.

According to Japanese Patent Unexamined Publication No. 2016-122918,attribute information related to the content of video data can be easilyassigned through a user's simple operation, and thus it can be said thatthe technique disclosed in Japanese Patent Unexamined Publication No.2016-122918 has high usefulness.

However, in the configuration disclosed in Japanese Patent UnexaminedPublication No. 2016-122918, it is not taken into consideration that awearable camera determines each of various behaviors (for example, aplurality of types of behaviors performed from the start of patrol tothe end thereof) performed by a user (for example, a police officer)wearing or carrying the wearable camera. Therefore, in the related artsuch as Japanese Patent Unexamined Publication No. 2016-122918,relevance between the content of a behavior performed by a user (forexample, a police officer) wearing or carrying a wearable camera and acaptured video during business cannot be recorded.

For example, in a case where a user (for example, a police officer)wearing or carrying a wearable camera returns to a police departmentfrom patrol, the user may create a case report in which behaviorsperformed on patrol are written in detail in a time series. In theabove-described configuration of the related art, each of behaviorsperformed by a police officer during recording of captured videos cannotbe determined. Thus, the police officer returns to a police department,and inevitably reproduces and watches captured videos recorded by thewearable camera. For example, as an appendix of the case report, thepolice officer is required to create a list on which behaviors performedin a time series on patrol are written. Therefore, a large amount ofcreation man-hours are necessary, and creation efficiency deteriorates.

SUMMARY

The present disclosure has been made in consideration of thecircumstances of the related art, and an object thereof is to provide awearable camera, a wearable camera system, and an information recordingmethod, in which, even if a user does not independently reproduce orwatch a recorded captured video, each of various behaviors of the userperformed in a time series is determined from a captured video recordedby the wearable camera, and is recorded as information, and business ofthe user is efficiently supported.

According to the present disclosure, there is provided a wearable camerawhich is able to be worn or carried by a user, including a videorecording device that records a captured video of a subject on the frontside of the user on a recorder; a sensor that acquires informationregarding motion of the user; a determiner that determines whether ornot at least one default event has occurred on the basis of informationregarding motion of the user acquired by the sensor during recording ofthe captured video of the subject; and a controller that generates eventlist information in which a detection time point of the default event iscorrelated with information regarding the default event according todetermination that the at least one default event has occurred duringrecording of the captured video of the subject, and records the eventlist information on the recorder in correlation with the captured videoof the subject.

According to the present disclosure, there is provided an informationrecording method using a wearable camera which is able to be worn orcarried by a user, the method including a step of recording a capturedvideo of a subject on the front side of the user on a recorder; a stepof acquiring information regarding motion of the user; a step ofdetermining whether or not at least one default event has occurred onthe basis of information regarding motion of the user acquired duringrecording of the captured video of the subject; and a step of generatingevent list information in which a detection time point of the defaultevent is correlated with information regarding the default eventaccording to determination that the at least one default event hasoccurred during recording of the captured video of the subject, andrecording the event list information on the recorder in correlation withthe captured video of the subject.

According to the present disclosure, there is provided a wearable camerasystem including a wearable camera that is able to be worn or carried bya user; and a server that is communicably connected to the wearablecamera, in which the wearable camera records a captured video of asubject on the front side of the user on a recorder, acquiresinformation regarding motion of the user during recording of thecaptured video of the subject, and transmits the acquired informationregarding motion of the user to the server, in which the server receivesthe information regarding motion of the user transmitted from thewearable camera, determines whether or not at least one default eventhas occurred on the basis of the received information regarding motionof the user, and transmits an instruction for generating event listinformation in which a detection time point of the default event iscorrelated with information regarding the default event to the wearablecamera according to determination that the at least one default eventhas occurred, and in which the wearable camera receives the instructionfor generating the event list information transmitted from the server,and generates the event list information in response to the receivedinstruction for generating the event list information, and records thegenerated event list information on the recorder in correlation with thecaptured video of the subject.

According to the present disclosure, there is provided a wearable camerasystem including a wearable camera that is able to be worn or carried bya user; and a server that is communicably connected to the wearablecamera, in which the wearable camera records a captured video of asubject on the front side of the user on a recorder, acquiresinformation regarding motion of the user, determines whether or not atleast one default event has occurred on the basis of informationregarding motion of the user acquired during recording of the capturedvideo of the subject, generates event list information in which adetection time point of the default event is correlated with informationregarding the default event according to determination that the at leastone default event has occurred during recording of the captured video ofthe subject, and records the event list information on the recorder incorrelation with the captured video of the subject, transmits thecaptured video of the subject recorded on the recorder and the eventlist information to the server in correlation with each other, and inwhich the server receives the captured video of the subject and theevent list information transmitted from the wearable camera, and recordsthe captured video of the subject recorded on the recorder and the eventlist information on a second recorder in correlation with each other.

According to the present disclosure, there is provided an informationrecording method using a wearable camera system including a wearablecamera that is able to be worn or carried by a user; and a server thatis communicably connected to the wearable camera, in which the wearablecamera records a captured video of a subject on the front side of theuser on a recorder, acquires information regarding motion of the userduring recording of the captured video of the subject, and transmits theacquired information regarding motion of the user to the server, inwhich the server receives the information regarding motion of the usertransmitted from the wearable camera, determines whether or not at leastone default event has occurred on the basis of the received informationregarding motion of the user, and transmits an instruction forgenerating event list information in which a detection time point of thedefault event is correlated with information regarding the default eventto the wearable camera according to determination that the at least onedefault event has occurred, and in which the wearable camera receivesthe instruction for generating the event list information transmittedfrom the server, and generates the event list information in response tothe received instruction for generating the event list information, andrecords the generated event list information on the recorder incorrelation with the captured video of the subject. According to thepresent disclosure, there is provided an information processingapparatus including a third recorder on which captured videos inwearable cameras respectively worn or carried by a plurality of users,and event list information including each detection time point of aplurality of types of default events detected during recording of thecaptured videos and information regarding each of the events arerecorded in correlation with the wearable cameras; a retrieval processorthat retrieves captured videos of an incident gaining attention from thecaptured videos recorded on the third recorder in response to entry of aretrieval condition; and a display controller that displays a retrievalresult screen including a list of a plurality of the captured videosextracted through the retrieval and a predetermined icon on a monitor,in which the display controller displays a video reproduction screenincluding the captured videos correlated with each of the wearablecameras and the event list information corresponding to the capturedvideos on the monitor in response to a selection operation on thepredetermined icon.

According to the present disclosure, there is provided an informationprocessing method using an information processing apparatus including athird recorder on which captured videos in wearable cameras respectivelyworn or carried by a plurality of users, and event list informationincluding each detection time point of a plurality of types of defaultevents detected during recording of the captured videos and informationregarding each of the events are recorded in correlation with thewearable cameras, the method including a step of retrieving capturedvideos of an incident gaining attention from the captured videosrecorded on the third recorder in response to entry of a retrievalcondition; a step of displaying a retrieval result screen including alist of a plurality of the captured videos extracted through theretrieval and a predetermined icon on a monitor; and a step ofdisplaying a video reproduction screen including the captured videoscorrelated with each of the wearable cameras and the event listinformation corresponding to the captured videos on the monitor inresponse to a selection operation on the predetermined icon.

According to the present disclosure, even if a user does notindependently reproduce or watch a recorded captured video, each ofvarious behaviors of the user performed in a time series can bedetermined from a captured video recorded by the wearable camera, so asto be recorded as information, and thus business of the user can beefficiently supported.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating a configuration example of awearable camera system of each exemplary embodiment;

FIG. 2 is a diagram illustrating an example of the upper half of thebody of a police officer wearing a wearable camera of each exemplaryembodiment;

FIG. 3 is a front view illustrating an example of a front surface of acasing of the wearable camera of each exemplary embodiment;

FIG. 4 is a block diagram illustrating a detailed example of an internalconfiguration of a wearable camera of Exemplary Embodiment 1 in detail;

FIG. 5 is a diagram illustrating an example of an action table regardingdetected actions;

FIG. 6 is a flowchart illustrating a detailed example of an action indexgeneration operation procedure in the wearable camera of ExemplaryEmbodiment 1;

FIG. 7 is an explanatory diagram illustrating an example of arelationship among detected actions, various pieces of measured data,and an action table;

FIG. 8 is a diagram illustrating examples of action indexes;

FIG. 9 is a diagram illustrating an example of an action map in whichinformation regarding positions where actions are detected in a timeseries is displayed to be superimposed on map data;

FIG. 10 is a flowchart illustrating a detailed example of an operationprocedure for generation of an action index or recording of capturedvideos in the wearable camera of Exemplary Embodiment 1;

FIG. 11 is a block diagram illustrating a detailed example of aninternal configuration of a back end server of Exemplary Embodiment 1;

FIG. 12 is a sequence diagram illustrating a detailed example of anaction index generation operation procedure, based on cooperationbetween the wearable camera and the back end server of ExemplaryEmbodiment 1;

FIG. 13A is a diagram illustrating an example in which the wearablecamera and an activity meter directly perform short-range radiocommunication with each other in the wearable camera system;

FIG. 13B is a diagram illustrating an example in which the wearablecamera and the activity meter perform short-range radio communicationwith each other via a smart phone in the wearable camera system;

FIG. 14 is a block diagram illustrating a detailed example of aninternal configuration of the activity meter;

FIG. 15 is a diagram illustrating an example of another action tableregarding detected actions;

FIG. 16 is a flowchart illustrating another detailed example of anaction index generation operation procedure in the wearable camera ofExemplary Embodiment 1;

FIG. 17 is a flowchart illustrating another detailed example ofgeneration or an action index or recording of a captured video in thewearable camera of Exemplary Embodiment 1;

FIG. 18 is a diagram illustrating an example of a retrieval resultscreen displaying an entry field for an action information retrievalcondition and a retrieval result;

FIG. 19 is an explanatory diagram illustrating an example in which awatching screen for a captured video is displayed on the basis ofpressing of a reproduction button corresponding to a certain record;

FIG. 20 is an explanatory diagram illustrating an example in whichlearning of measured data is started on the basis of rewriting of anaction information name in an action table;

FIG. 21 is a sequence diagram illustrating a detailed example of anoperation procedure regarding learning of measured data and update of alearning result, based on cooperation among a wearable camera, a backend server, and a back end client in a modification example of ExemplaryEmbodiment 1;

FIG. 22 is a flowchart illustrating a detailed example of an operationprocedure of sending a notification to an investigation headquarter onthe basis of detection of a default action in a wearable camera ofExemplary Embodiment 2;

FIG. 23 is a flowchart illustrating a detailed example of a datatransmission operation procedure after the notification is sent to theinvestigation headquarter in the wearable camera of Exemplary Embodiment2;

FIG. 24 is a schematic diagram illustrating a configuration example of awearable camera system of Exemplary Embodiment 3;

FIG. 25 is a diagram illustrating a configuration example of videoaccumulation data recorded in a back end server of Exemplary Embodiment3;

FIG. 26 is a sequence diagram illustrating a detailed example of ananalysis operation procedure for captured video data transmitted from awearable camera or a monitoring camera in the back end server ofExemplary Embodiment 3;

FIG. 27 is a block diagram illustrating a detailed example of aninternal configuration of a back end client of Exemplary Embodiment 4;

FIG. 28 is a diagram illustrating an example of a retrieval resultscreen displaying an entry field for a captured video retrievalcondition and a retrieval result;

FIG. 29 is a diagram illustrating an example of a multi-simultaneousreproduction screen based on pressing of a multi-simultaneousreproduction button in the retrieval result screen in FIG. 28;

FIG. 30 is a diagram illustrating another example of amulti-simultaneous reproduction screen;

FIG. 31 is a diagram illustrating examples of output videos based on apredetermined format;

FIG. 32 is a flowchart illustrating a detailed example of a displayoperation procedure corresponding to a captured video retrievalinstruction in the back end client of Exemplary Embodiment 4;

FIG. 33A is a diagram illustrating a first example of a case basis eventhistory list corresponding to a case basis unique event list in amodification example of Exemplary Embodiment 4;

FIG. 33B is a diagram illustrating a second example of a case basisevent history list corresponding to a case basis unique event list in amodification example of Exemplary Embodiment 4;

FIG. 34 is a diagram illustrating another example of a retrieval resultscreen displaying an entry field for a captured video retrievalcondition and a retrieval result;

FIG. 35 is a diagram illustrating a first example of amulti-simultaneous reproduction screen based on pressing of amulti-simultaneous reproduction button in the retrieval result screen inFIG. 34;

FIG. 36A is a diagram illustrating an example of a case basis eventhistory list of a police officer A with an identification number“HP2345”;

FIG. 36B is a diagram illustrating an example of a case basis eventhistory list of a police officer B with an identification number“HP3456”;

FIG. 37A is a diagram illustrating an example of a case basis eventhistory list into which the policemen A and B with the identificationnumbers “HP2345” and “HP3456” are merged; and

FIG. 37B is a diagram illustrating an example of an action map in whicheinformation regarding positions where actions in the case basis eventhistory lists in FIGS. 36A and 36B are detected is displayed to besuperimposed on map data.

DETAILED DESCRIPTION

History of Reaching Exemplary Embodiment 1

In the configuration disclosed in Japanese Patent Unexamined PublicationNo. 2016-122918, it is not taken into consideration that a wearablecamera determines each of various behaviors (for example, a plurality oftypes of behaviors performed from the start of patrol to the endthereof) performed by a user (for example, a police officer) wearing orcarrying the wearable camera. Therefore, in the related art such asJapanese

Patent Unexamined Publication No. 2016-122918, relevance between thecontent of a behavior performed by a user (for example, a policeofficer) wearing or carrying a wearable camera and a captured videoduring business cannot be recorded.

For example, in a case where a user (for example, a police officer)wearing or carrying a wearable camera returns to a police departmentfrom patrol, the user may create a case report in which behaviorsperformed on patrol are written in detail in a time series. In theabove-described configuration of the related art, each of behaviorsperformed by a police officer during recording of captured videos cannotbe determined. Thus, the police officer returns to a police department,and inevitably reproduces and watches captured videos recorded by thewearable camera. For example, as an appendix of the case report, thepolice officer is required to create a list on which behaviors performedin a time series on patrol are written. Therefore, a large amount ofcreation man-hours are necessary, and creation efficiency deteriorates.

Therefore, in Exemplary Embodiment 1, in light of the circumstances, adescription will be made of examples of a wearable camera, a wearablecamera system, and an information recording method, in which, even if auser does not independently reproduce or watch captured videos whichhave been recorded, each of various behaviors performed by the user in atime series is determined to be recorded as information, and thus theuser's business is efficiently supported.

Hereinafter, with reference to the accompanying drawings as appropriate,a detailed description of each exemplary embodiment in which a wearablecamera, a wearable camera system, and an information recording methodaccording to the present disclosure are specifically disclosed. However,a detailed description more than necessary will be omitted in somecases. For example, a detailed description of the well-known content ora repeated description of the same configuration will be omitted in somecases. This is for avoiding unnecessary redundancy of the followingdescription and enabling a person skilled in the art to easilyunderstand the present disclosure. The accompanying drawings and thefollowing description are provided for a person skilled in the art tosufficiently understand the present disclosure, and are not intended tolimit the spirit disclosed in the claims.

In the following respective exemplary embodiments, a police officer willbe exemplified as a user of a wearable camera according to the presentdisclosure. However, a user of a wearable camera according to thepresent disclosure is not limited to a police officer, and may be asecurity guard, and may be a common citizen instead of a police officeror a security guard.

Exemplary Embodiment 1

FIG. 1 is a schematic diagram illustrating a configuration example ofwearable camera system 1000 of each exemplary embodiment. Wearablecamera system 1000 illustrated in FIG. 1 includes wearable camera 10which can be worn or carried by a police officer; various apparatusesdisposed in police department PD; various apparatuses used in a field bya police officer; various apparatuses used or mounted in police vehicle7 (for example, a patrol car; the same applies hereinafter); and variousapparatuses used in an officer home.

Wearable camera 10 may be included in any of the various apparatusesdisposed in police department PD, the various apparatuses used in afield by a police officer, the various apparatuses used or mounted inpolice vehicle 7, and the various apparatuses used in the officer home.

The various apparatuses disposed in police department PD includes, forexample, at least back end server (BES) 50, back end streaming server(BSS) 60, back end clients (BECs) 70 a and 70 b, wireless local areanetwork (LAN) access point 63, and a gang charger which can collectivelycharge a plurality of wearable cameras as an example of a chargingdevice, but are not limited thereto.

The various apparatuses used in a field by a police officer include, forexample, at least smart phone 40 (which may also be a tablet terminal)which can be carried by a police officer, and wireless LAN access point45 which can be carried by a police officer, but are not limitedthereto. Smart phone 40 and wireless LAN access point 45 are carried,for example, within a pocket of a uniform worn by a police officer.

The various apparatuses used or mounted in police vehicle 7 include, forexample, at least in-car camera system (in-car video: ICV) 30, in-car PC32, common trigger box (CTB) 100 as an example of an in-carcommunication apparatus, a charging cradle as an example of a chargingdevice (pairing dock), and a rotary warning light PL, but are notlimited thereto.

The various apparatuses used in the officer home include, for example,at least a cradle for charging wearable camera 10 and a home router, butare not limited thereto.

In-car camera system 30 includes one or a plurality of in-car cameras31, in-car PC 32, and in-car recorder 33, and images and records a caseencountered during traveling with police vehicle 7 or a situation onpatrol as videos. One or plurality of in-car cameras 31 include, forexample, one or a plurality of cameras among a camera provided to imagethe front side of police vehicle 7, and cameras respectively provided toimage the left side, the right side, and the rear side of police vehicle7. In-car PC 32 controls operations of in-car cameras 31 and in-carrecorder 33 in response to an operation performed by police officer 3.In-car recorder 33 records data regarding videos captured by each of theplurality of in-car cameras 31 in a time series. In a case where in-carPC 32 is connected to wearable camera 10 via the Universal Serial Bus(USB), in-car PC 32 charges wearable camera 10, acquires data regardingvideos captured by wearable camera 10 via the USB, and reproduces thevideos in a default application installed in in-car PC 32, or assignsattribute information to the videos in the application in response tothe police officer's operation.

In-car camera system 30 is connected to common trigger box 100 in awired manner (for example, LAN communication), and performs an operation(for example, starting or stopping of recording of data regarding videoscaptured by in-car cameras 31) corresponding to a command from commontrigger box 100. In-car camera system 30 is communicably connected towearable camera 10 via common trigger box 100, and starts recording within-car recorder 33 at the same timing as a timing at which wearablecamera 10 starts imaging. Conversely, in-car recorder 33 may startrecording at the same timing as a timing at which wearable camera 10starts imaging. In-car camera system 30 may record videos captured bywearable camera 10 in in-car recorder 33.

Wearable camera 10 is mounted or held on a uniform of a police officeras an example of a user. Wearable camera 10 images a situation as asubject on the front side of the police officer, and transmits videodata obtained through the imaging to in-car camera system 30 via commontrigger box 100, or wearable camera 10 and in-car recorder 33simultaneously start imaging. Wearable camera 10 directly transmits thevideo data to back end server 50 via wireless LAN access point 63, orstreams the video data to back end streaming server 60 via smart phone40 or wireless LAN access point 45 and network NW1 (for example, amobile communication network or the Internet). In police department PD,wearable camera 10 may send the captured video data to back end client70 b connected thereto via the USB, or to back end server 50 connectedthereto via a LAN in police department PD. Wearable camera 10 may bemanually mounted on a charging surface of the gang charger so as totransmit the captured video data to back end server 50.

An imaging target subject of wearable camera 10 or in-car cameras 31includes not only a person, but also a building, a square, a scene of acase field, a crowd (so-called onlookers) gathering near the field, andan atmosphere around an imaging position. In the following description,the field refers to a location where a decisive moment about a case (forexample, arson, murder, injury, or robbery) was witnessed. Policeofficer 3 may carry smart phone 40 or wireless LAN access point 45 as anexample of a wireless terminal which can perform communication withwearable camera 10. Smart phone 40, which has a telephone function and awireless communication function (for example, a dithering function), isused for emergency contact from police department PD or emergencycontact to police department PD, and relays data from wearable camera 10to back end streaming server 60 in police department PD. In response tothe police officer's operation, smart phone 40 reproduces captured videodata obtained by wearable camera 10 or edits the captured video data byassigning attribute information (metadata) thereto.

Wireless LAN access point 45 relays data from wearable camera 10 to backend streaming server 60 in police department PD. Wireless communication(for example, Bluetooth (registered trademark) Low Energy (BLE)) or awireless LAN (WLAN, for example, WiFi (registered trademark)) is usedbetween wearable camera 10 and smart phone 40 or wireless LAN accesspoint 45. In a case of high speed communication such as wearable camera10 streaming data to back end streaming server 60 via smart phone 40 orwireless LAN access point 45, wireless communication using a fastwireless LAN in which a transmission speed is higher than that of BLE isemployed. On the other hand, in a case of low speed communication suchas data such as a case number of a captured video obtained by wearablecamera 10 being edited in smart phone 40, wireless communication usingBLE is employed.

Back end server 50 is configured to include a computer and a storage,and manages evidence videos of a case. Back end server 50 has, forexample, a video analysis function such as a face recognition functionof recognizing a face in image frames forming videos captured bywearable camera 10 or in-car cameras 31 or an editing function ofediting at least some of the videos through image processing in responseto a request corresponding to an operation performed by a user (forexample, police officer 3 or a specialist for analysis in policedepartment PD) using back end clients 70 a and 70 b. Back end server 50has, for example, a reproduction function of reproducing videos capturedby wearable camera 10 or in-car cameras 31 in response to a requestcorresponding to an operation performed by a user (for example, policeofficer 3 or a specialist for analysis in police department PD) usingback end clients 70 a and 70 b.

Back end streaming server 60 receives video data streamed from wearablecamera 10, and transmits the video data to back end server 50.

Each of back end clients 70 a and 70 b is formed of, for example, a PC,and has a browser or a dedicated application which accesses a suspiciousperson database (DB) (not illustrated) in back end server 50, retrievesinformation regarding a case related to a criminal or the like, and candisplay a retrieval result on a display device (a liquid crystal display(LCD) provided in each of back end clients 70 a and 70 b). For example,a person wanted or a past criminal is registered in advance incorrelation with information (for example, a case number) foridentifying a case in suspicious person DB. Back end clients 70 a and 70b may access voice DB of back end server 50 and retrieve voiceinformation regarding a case related to a criminal or the like. Back endclients 70 may be provided not only inside police department PD but alsooutside police department PD. Back end clients 70 may be thin client PCsor rich client PCs.

Wireless LAN access point 63 is connected to wearable camera 10 via awireless LAN (WLAN), and relays video data transmitted from wearablecamera 10 to back end server 50.

The gang charger allows wearable camera 10 worn or carried by each of aplurality of police officers to be mounted on a predetermined chargingsurface, and charges a battery of each mounted wearable camera 10. Thegang charger has a function of performing wired communication withwearable camera 10 during charging, and transmitting video data storedin wearable camera 10 to back end server 50. Alternatively, wearablecamera 10 may directly perform communication with back end server 50through a LAN interface (not illustrated) via the gang charger. The gangcharger is connected to back end client 70 b via a Universal Serial Bus(USB) cable in a wired manner.

Common trigger box 100 is connected to rotary warning light PL, a siren(not illustrated), in-car camera system 30, and the charging cradle in awired manner (for example, LAN communication), and can be connected towearable camera 10 via the charging cradle when wearable camera 10 isconnected to the charging cradle. Common trigger box 100 sends a controlsignal for recording starting or recording stopping by using

BLE or a wireless LAN (WLAN) between an apparatus (hereinafter, referredto as a “CTB connected apparatus” in some cases) connected to commontrigger box 100 in a wired or wireless manner and wearable camera 10,and thus controls execution of recording starting or recording stoppingsynchronized between wearable camera 10 and the CTB connected apparatus.The CTB connected apparatus is, for example, the above-described rotarywarning light PL, siren (not illustrated), in-car camera system 30 orcharging cradle.

In a case where common trigger box 100 is connected to, for example,in-car camera system 30 in a wired manner (for example, LANcommunication), common trigger box 100 sends a control signal forrecording starting or recording stopping to in-car camera system 30.Consequently, in-car camera system 30 may start recording of dataregarding videos captured by in-car cameras 31 on in-car recorder 33 ormay stop the recording as an operation corresponding to the controlsignal from common trigger box 100. If an operation starting signal isacquired from a police vehicle mounted vehicle such as rotary warninglight PL or the siren, common trigger box 100 detects the start of useof the police vehicle mounted apparatus, and sends a control signal forrecording starting or recording stopping to wearable camera 10 or in-carcamera system 30 connected to common trigger box 100. Consequently,wearable camera 10 or in-car camera system 30 may start recording ofdata regarding videos obtained through imaging due to, for example,rotation starting of rotary warning light PL or sound outputting of thesiren, or may stop the recording, as an operation corresponding to thecontrol signal from common trigger box 100.

In a case where common trigger box connected apparatuses are only in-carrecorder 33 and wearable camera 10, if one (for example, in-car recorder33) sends a notification that recording is started or stopped to commontrigger box 100, common trigger box 100 sends a control signal forrecording starting or stopping to the other apparatus (for example,wearable camera 10). Consequently, common trigger box 100 can cause bothof in-car recorder 33 and wearable camera 10 to start or stop recordingsubstantially simultaneously.

The charging cradle is disposed, for example, at a default position (forexample, near a center console) of police vehicle 7, and is connected tocommon trigger box 100 in a wired manner (for example, Power overEthernet (registered trademark) (PoE) using a LAN cable). The chargingcradle has the charging surface for mounting wearable camera 10. In acase where the charging cradle is connected to common trigger box 100 ina wired manner (for example, PoE using a LAN cable), and is connected towearable camera 10 due to wearable camera 10 being mounted on thecharging surface, the charging cradle can charge the battery of wearablecamera 10 on the basis of a current supplied from common trigger box100.

It is assumed that a police officer mounts wearable camera 10 on acradle corresponding to wearable camera 10 when returning to the officerhome or on break. In this case, wearable camera 10 can transmit dataregarding videos captured by wearable camera 10 to back end server 50via the home router which is connected to the cradle in a wired manner(for example, LAN communication) and network NW2.

FIG. 2 is a diagram illustrating an example of the upper half of thebody of police officer 3 wearing wearable camera 10 of each exemplaryembodiment. Wearable camera 10 is mounted or held on a front part of auniform of police officer 3 so as to image the front side of policeofficer 3. Wearable camera 10 may be fixed to the front part of theuniform in a state of being suspended from the neck with a string, forexample. Wearable camera 10 may be fixed to the front part of theuniform as a result of an attachment tool (for example, an attachmentclip) attached to a rear surface of casing 10 z (refer to FIG. 3) ofwearable camera 10 being engaged with an attachment tool attached to thefront part of the uniform.

FIG. 3 is a front view illustrating an example of a front surface ofcasing 10 z of wearable camera 10 of each exemplary embodiment.Recording switch SW1, snapshot switch SW2, and imaging lens 11 z aredisposed on the front surface of casing 10 z. Processor 19 detects anoperation on each of recording switch SW1 and snapshot switch SW2, andperforms a process on a switch input corresponding to the operation.

Recording switch SW1 is pressed for a short period of time and thusgives an instruction for recording starting, and is pressed for a longperiod of time (for example, an operation in which a pressing state iscontinued for three seconds) and thus gives an instruction for recordingstopping. Processor 19 may execute recording starting or may executerecording stopping in response to such an instruction. Snapshot switchSW2 gives an instruction for recording a still image captured by capture11, for example, when being pressed. Processor 19 may record a stillimage in response to such an instruction. Imaging lens 11 z forms anoptical image captured by wearable camera 10 on an imaging surface ofcapture 11 (refer to FIG. 4).

Communication mode switch SW3 and attribute information assignmentswitch SW4 are disposed on a side surface of casing 10 z. Processor 19detects an operation on each of communication mode switch SW3 andattribute information assignment switch SW4, and performs a process on aswitch input corresponding to the operation.

Attribute information assignment switch SW4 is a pressing type buttonswitch which is operated in order to assign attribute information tovideo data. In a case where attribute information assignment switch SW4is pressed, processor 19 assigns attribute information to cutout dataincluding a face image which is cut out from a captured image obtainedby capture 11.

Communication mode switch SW3 is, for example, a slide switch forinputting an operation instruction for setting a communication modebetween wearable camera 10 and an external apparatus. Processor 19detects a state of communication mode switch SW3, and operates BLEcommunicator 21A or WLAN communicator 21B according to a communicationmode corresponding to setting of communication mode switch SW3.

The communication mode includes, for example, an access point mode, astation mode, and an OFF mode. The access point mode is a mode in whichwearable camera 10, which operates as an access point of a wireless LAN,is wirelessly connected to, for example, smart phone 40 carried bypolice officer 3, and thus wearable camera 10 and smart phone 40 performcommunication with each other. In the access point mode, smart phone 40may be connected to wearable camera 10 so as to perform display of thecurrent live images in wearable camera 10, reproduction of recordedimages, display of captured still images, and the like. The station modeis a mode in which, in a case of being connected to an externalapparatus by using a wireless LAN, communication is performed by usingthe external apparatus as an access point. For example, smart phone 40may be set as an external apparatus by using the dithering function ofsmart phone 40. In the station mode, wearable camera 10 may transmit(upload) various settings, recorded images held in wearable camera 10,and the like, to in-car camera system 30, or back end clients 70 or backend server 50 in police department PD. For example, three LEDs 26 a, 26b and 26 c are disposed on an upper surface of casing 10 z. LED 26 adisplays a state of power on/off of wearable camera 10 and a state ofbattery 25 (refer to FIG. 4). LED 26 b displays a state of an imagingoperation of wearable camera 10. LED 26 c displays a state of acommunication mode of wearable camera 10.

FIG. 4 is a block diagram illustrating a detailed example of an internalconfiguration of wearable camera 10 of Exemplary Embodiment 1. Wearablecamera 10 includes capture 11, memory 13, recorder 15, globalpositioning system (GPS) receptor 18, and processor 19.

Wearable camera 10 includes BLE communicator 21A, WLAN communicator 21B,and USB interface 22. Wearable camera 10 includes battery 25, LEDcontroller 26, vibrator 27, microphone 29A, speaker 29B, and earphoneterminal 29C. Wearable camera 10 includes acceleration sensor AC andgyro sensor GY.

Capture 11 is configured to include imaging lens 11 z (refer to FIG. 3),and a solid-state imaging element such as a charge coupled device (CCD)type image sensor or a complementary metal oxide semiconductor (CMOS)type image sensor. While a power source of wearable camera 10 is turnedon, capture 11 normally outputs data regarding a captured image of asubject obtained on the basis of imaging in the solid-state imagingelement, to processor 19. The captured image data is input tovideo/sound data generator 19A of processor 19.

Memory 13 is formed by using, for example, a random access memory (RAM)and a read only memory (ROM), and temporarily stores a program or datarequired to perform an operation of wearable camera 10 and furtherinformation or data generated during the operation. The RAM is, forexample, a work memory used during an operation of processor 19. The ROMstores, for example, a program and data used to control processor 19 inadvance. Memory 13 stores, for example, identification information (forexample, a serial number) for identifying wearable camera 10, andvarious pieces of setting information.

Recorder 15 is formed by using a semiconductor memory (for example, aflash memory) built into wearable camera 10 or an external storagemedium such as a memory card (for example, an SD card) not built intowearable camera 10. Recorder 15 records an action index AL1 (refer toFIG. 9) generated by action information generator 19D of processor 19 ordata regarding action map MP1 in correlation with a captured video orvoice data corresponding to action index AL1 or action map MP1. Recorder15 normally pre-buffers and holds captured video data corresponding to apredetermined time, and continuously accumulates captured video datacorresponding to a predetermined time (for example, thirty seconds)before the current time. If a recording starting instruction is receivedfrom processor 19, recorder 15 starts to record captured video data, andcontinuously records the captured video data until a recording stoppinginstruction is received from processor 19. In a case where recorder 15is formed of a memory card, recorder 15 is detachably attached to casing10 z of wearable camera 10.

GPS receptor 18 receives satellite signals transmitted from a pluralityof GPS signal transmitters (for example, four navigation satellites),each including a signal transmission time and a position coordinatethereof. GPS receptor 18 (position information acquisition) calculatesthe current position coordinate of wearable camera 10 and receptiontimes of the satellite signals by using the plurality of satellitesignals. This calculation may be performed by processor 19 to which anoutput from GPS receptor 18 is input instead of GPS receptor 18.Information regarding a reception time may be used to correct a systemtime (that is, an output from clock 17) of wearable camera 10. Thesystem time is used for recording of an imaging time of a captured image(including a still image and a moving image) or as times of detectingvarious actions (refer to FIG. 5) as default events.

Processor 19 functions as a controller of wearable camera 10, andperforms a control process of integrating operations of the respectiveconstituent elements of wearable camera 10 as a whole, a process oftransmitting and receiving data to and from the respective constituentelements of wearable camera 10, a data calculation (computation)process, and a data storage process. Processor 19 is operated accordingto the program and the data stored in memory 13. During an operation,processor 19 acquires the current time information from clock 17 andacquires the current position information from GPS receptor 18 by usingmemory 13.

Processor 19 is formed by using, for example, a central processing unit(CPU), a micro processing unit (MPU), a digital signal processor (DSP),or a field programmable gate array (FPGA). Processor 19 is configured toinclude clock 17, video/sound data generator 19A, sensor data analyzer19B, video/sound data analyzer 19C, and action information generator19D, as software functional configurations.

Clock 17 counts information regarding the current time (that is, asystem time of wearable camera 10), and outputs the counted informationto GPS receptor 18 and action information generator 19D.

While the power source of wearable camera 10 is turned on, video/sounddata generator 19A normally receives captured image data which is outputfrom capture 11. Video/sound data generator 19A converts the capturedimage data output from capture 11 into data with a data format such thatthe data can be recorded (stored) in recorder 15. In other words,video/sound data generator 19A (video recording device) generates dataregarding captured videos of a subject on the front side of a user (forexample, police officer 3), and records the data on recorder 15.Video/sound data generator 19A outputs data regarding captured videos ofa subject on the front side of a user (for example, police officer 3) tovideo/sound data analyzer 19C.

While the power source of wearable camera 10 is turned on, video/sounddata generator 19A normally receives sound data which is output from themicrophone 29A. Video/sound data generator 19A converts the sound dataoutput from microphone 29A into data with a data format such that thedata can be recorded (stored) on recorder 15. In other words,video/sound data generator 19A (sound recorder) generates sound dataaround a user (for example, police officer 3), and records the sounddata on recorder 15. Video/sound data generator 19A outputs sound dataaround a user (for example, police officer 3) to video/sound dataanalyzer 19C.

While the power source of wearable camera 10 is turned on, sensor dataanalyzer 19B normally receives acceleration data in three-axis (an xaxis, a y axis, and a z axis) directions of an orthogonal coordinatesystem, measured by acceleration sensor AC or inclination data inthree-axis (an x axis, a y axis, and a z axis) directions of anorthogonal coordinate system, measured by gyro sensor GY. Sensor dataanalyzer 19B outputs the acceleration data and the inclination data fromacceleration sensor AC and gyro sensor GY to action informationgenerator 19D.

Video/sound data analyzer 19C performs a predetermined analysis processon the data regarding the captured videos of the subject on the frontside of the user (for example, police officer 3) or the sound dataaround the user (for example, police officer 3) sent from video/sounddata generator 19A, and outputs an analysis result to action informationgenerator 19D. Video/sound data analyzer 19C analyzes whether or notpolice officer 3 takes out and levels a gun at a criminal of a seriouscase in front of police officer 3 by using, for example, the dataregarding the captured videos of the subject on the front side of theuser (for example, police officer 3). Video/sound data analyzer 19Canalyzes whether or not the user (for example, police officer 3) said adefault phrase (for example, “freeze”) for urging a suspicious personsuch as a suspect in front thereof or in pursuit to stop by using, forexample, the sound data around the user (for example, police officer 3).

Action information generator 19D acquires the current time informationoutput from clock 17, the current position information of wearablecamera 10 output from GPS receptor 18, and the acceleration data and theinclination data in the three-axis (the x axis, the y axis, and the zaxis) directions of the orthogonal coordinate system, sent from sensordata analyzer 19B. Action information generator 19D acquires dataregarding the analysis result sent from video/sound data analyzer 19C.

Action information generator 19D (determiner) determines whether or notat least one default event has occurred on the basis of one or both ofthe acceleration data acquired (specifically, measured) by accelerationsensor AC and the inclination data acquired (specifically, measured) bygyro sensor GY during recording of captured videos of a subject. Aspecific example of the default event will be described later withreference to FIG. 5. In the present exemplary embodiment, the defaultevent indicates behaviors (hereinafter, for convenience, referred to as“actions” in some cases) of a user (for example, police officer 3)performed in a time series during business (for example, on patrol or inpursuit of a suspicious person such as a criminal), or symptoms of theuser (for example, police officer 3) appearing in a time series.

FIG. 5 is a diagram illustrating an example of action table Atb0regarding detected actions. In action table Atb0, for example, thecontent of each default event (for example, an action) stored in memory13 or recorder 15 is correlated with a sensor used for detection of eachdefault event (for example, an action), or a detection condition. In thepresent exemplary embodiment, detected events (for example, actions) arenot limited to events listed in FIG. 5. Action information generator 19Drefers to action table Atb0, and determines whether or not theabove-described default event has occurred on the basis of measured data(specifically, one or both of acceleration data and inclination data) ina sensor used for detection of the default event or whether or not adetection condition has been established.

For example, in a case of detecting whether or not police officer 3started to run as an action, one or both of acceleration data measuredby acceleration sensor AC and inclination data measured by gyro sensorGY are referred to.

For example, in a case of detecting whether or not police officer 3 felldown or was shot as an action, one or both of acceleration data measuredby acceleration sensor AC and inclination data measured by gyro sensorGY are referred to.

For example, in a case of detecting whether or not police officer 3 tooka gun from a holster as an action, one or both of acceleration datameasured by acceleration sensor AC and inclination data measured by gyrosensor GY are referred to.

For example, in a case of detecting whether or not police officer 3 heldthe gun at the ready as an action, all of acceleration data measured byacceleration sensor AC, inclination data measured by gyro sensor GY, anddata measured by a sensor (not illustrated) attached to the holster arereferred to. Although not illustrated in FIG. 5, in a case of detectingwhether or not police officer 3 held the gun at the ready as an action,a video analysis result in video/sound data analyzer 19C may be referredto along with or instead of acceleration data measured by accelerationsensor AC, inclination data measured by gyro sensor GY, and datameasured by a sensor (not illustrated) attached to the holster.

For example, in a case of detecting whether or not police officer 3 gotoff a vehicle (for example, police vehicle 7) as an action, accelerationdata measured by acceleration sensor AC is referred to.

For example, in a case of detecting whether or not police officer 3conducts an interview as an action, it is referred to whether or notpolice officer 3 stops on the basis of acceleration data measured byacceleration sensor AC and inclination data measured by gyro sensor GY,and whether or not police officer 3 has a conversation as a soundanalysis result in video/sound data analyzer 19C.

For example, in a case of detecting whether or not police officer 3urged stoppage as an action, it is referred to whether or not “freeze”is recognized as voices as a sound analysis result in video/sound dataanalyzer 19C.

In a case where it is determined that at least one default event hasoccurred, action information generator 19D generates event listinformation (for example, action index AL1; refer to FIG. 8) in which adetection time point of the default event is correlated with informationregarding the default event. Action information generator 19D recordsaction index AL1 on recorder 15 in correlation with captured videosrecorded on recorder 15 by video/sound data generator 19A. Action indexAL1 will be described later with reference to FIG. 8.

In a case where it is determined that at least one default event hasoccurred, action information generator 19D acquires captured video dataof a subject from video/sound data generator 19A, and generates athumbnail image corresponding to a detection time point of the defaultevent. Action information generator 19D records action index AL1including the generated thumbnail image on recorder 15.

In a case where it is determined that at least one default event hasoccurred, action information generator 19D acquires position informationof wearable camera 10 corresponding to a detection time point of thedefault event. Action information generator 19D reads, for example, mapdata MP0 stored in recorder 15, generates action map MP1 in which theposition information is superimposed on map data MP0, and records actionmap MP1 on recorder 15.

BLE communicator 21A (communicator) performs wireless communication withsmart phone 40 or the like by using a communication form of Bluetooth(registered trademark) Low Energy (BLE) which is a communicationstandard related to short-range radio communication. BLE is the name ofthe version 4.0 of Bluetooth (registered trademark). In BLE,communication is possible at low power consumption, but a communicationspeed is low as 100 kbps.

In a case where smart phone 40 operates as an access point by using thedithering function, WLAN communicator 21B (communicator) is connected tosmart phone 40 or wireless LAN access point 63 in police department PDvia a wireless LAN (that is, a WLAN). WLAN communicator 21B performswireless communication (for example, WiFi (registered trademark)communication) with an apparatus as a connection destination of thewireless LAN. The wireless LAN enables high speed communication as acommunication speed of several tens to several hundreds of Mbps comparedwith BLE, but is connected to a wireless LAN access point at all times,so that power consumption increases.

Wearable camera 10 may have a configuration (not illustrated) of acommunicator for performing wireless communication using short-rangeradio communication such as Near Field Communication (NFC), a wide areamobile line network (for example, Long Term Evolution (LTE)), or theFifth Generation Mobile Communications System (5G), in addition to BLEcommunication or WLAN communication.

USB interface 22 is a serial bus, and enables wired connection to, forexample, in-car camera system 30 or back end clients 70 in policedepartment PD.

Battery 25 is formed of, for example, a rechargeable secondary battery,and supplies source power to the respective constituent elements ofwearable camera 10.

LED controller 26 controls, for example, lighting or unlightingoperations of three LEDs 26 a, 26 b and 26 c according to an operationstate of wearable camera 10.

Vibrator 27 vibrates in a predetermined vibration pattern on the basisof an instruction from processor 19 according to an operation state ofwearable camera 10. A single type or a plurality of types of vibrationpatterns may be used.

Microphone 29A (sound collector) collects sounds around wearable camera10 (in other words, police officer 3), and outputs sound data of thecollected sounds to processor 19. The sound data is input to video/sounddata generator 19A of processor 19. Microphone 29A may be a built-inmicrophone accommodated in casing 10 z of wearable camera 10, and may bea wireless microphone which is wirelessly connected to wearable camera10. In a case of the wireless microphone, police officer 3 attaches themicrophone to any location, and can increase sound collection property.

Speaker 29B (sound output) outputs a sound signal sent from processor 19as sounds. Speaker 29B outputs a sound signal for outputting apredetermined sound by reading a default sound stored in advance inmemory 13 (for example, the read only memory (ROM)) or combining aplurality of types of sounds.

Earphone terminal 29C is a connector connected to an earphone (notillustrated), and outputs a sound signal which is output as a sound fromspeaker 29B, to the earphone during connection to the earphone.

Although not illustrated in FIG. 4, recording switch SW1, snapshotswitch SW2, communication mode switch SW3, attribute informationassignment switch SW4, LEDs 26 a, 26 b and 26 c are connected toprocessor 19 via a GPIO which is a parallel interface via which signalsare input and output. Vibrator 27, microphone 29A, speaker 29B, andearphone terminal 29C are illustrated to be directly connected toprocessor 19 in FIG. 4, but may be similarly connected thereto via theGPIO which is a parallel interface.

Gyro sensor GY (sensor) detects and measures angular velocities (thatis, rotation angles or inclinations of wearable camera 10 or policeofficer 3 per unit time wearing wearable camera 10) in the three-axis(the x axis, the y axis, and the z axis) directions of the orthogonalcoordinate system of wearable camera 10. In other words, gyro sensor GYmay acquire information regarding motion of police officer 3 wearingwearable camera 10. For example, gyro sensor GY detects that policeofficer 3 wearing or carrying wearable camera 10 fell down (man down). Adetection result in gyro sensor GY is input to processor 19 via an I2C(not illustrated). Wearable camera 10 can detect behaviors (for example,that police officer 3 fell to the ground, was shot and fell to theground, and was attacked by a weapon and fell to the ground) regardingrotations of police officer 3 wearing or carrying wearable camera 10with high accuracy by using gyro sensor GY. Inclination data in thethree-axis directions measured by gyro sensor GY is referred to when itis determined whether or not various actions illustrated in FIG. 5 weredetected.

Acceleration sensor AC (sensor) detects and measures accelerations inthe three-axis (the x axis, the y axis, and the z axis) directions ofthe orthogonal coordinate system of wearable camera 10. In other words,acceleration sensor AC may acquire information regarding motion ofpolice officer 3 wearing wearable camera 10. For example, accelerationsensor AC detects that police officer 3 wearing or carrying wearablecamera 10 fell down (man down), police officer 3 started to run, andpolice officer 3 took a shooting posture with the possessed gun. Adetection result in acceleration sensor AC is input to processor 19 viaan I2C (not illustrated). Wearable camera 10 can detect behaviorsregarding motion or a body posture of police officer 3 wearing orholding wearable camera 10 with high accuracy by using accelerationsensor AC. Inclination data in the three-axis directions measured byacceleration sensor AC is referred to when it is determined whether ornot various actions illustrated in FIG. 5 were detected.

Although not illustrated in FIG. 4, gyro sensor GY and accelerationsensor AC are connected to processor 19 via a communication interfacesuch as an inter-integrated circuit (I2C).

FIG. 6 is a flowchart illustrating a detailed example of a generationoperation procedure for action index AL1 in wearable camera 10 ofExemplary Embodiment 1. FIG. 6 will be described assuming that the powersource of wearable camera 10 is in an ON state.

In FIG. 6, since the power source is turned on, wearable camera 10images a subject on the front side of police officer 3 with capture 11(S1). After step S1, wearable camera 10 determines whether or not dataregarding captured videos obtained in step S1 is being recorded (S2). Ina case where the data is not being recorded (S2: NO), the process inwearable camera 10 returns to step S1.

On the other hand, for example, in a case where recording switch SW1 ispressed for a short period of time, processor 19 of wearable camera 10determines that the data regarding captured videos is being recorded(S2: YES), and performs a process in step S3. In other words, inwearable camera 10, processor 19 acquires acceleration data andinclination data in the three-axis directions of the orthogonalcoordinate system measured by acceleration sensor AC and gyro sensor GY(S3).

In wearable camera 10, action information generator 19D acquires dataregarding a sound analysis result delivered from video/sound dataanalyzer 19C (S4). In wearable camera 10, action information generator19D acquires data regarding a video analysis result delivered fromvideo/sound data analyzer 19C (S5). An order of the processes in stepsS3 to S5 may be any order.

In wearable camera 10, action information generator 19D refers to actiontable Atb1 (refer to FIG. 7), and determines an action of police officer3 by using at least two types of measured data among the four types ofmeasured data (that is, the acceleration data and the inclination datain the three-axis directions of the orthogonal coordinate system, thesound analysis result data, and the video analysis result data) acquiredin the respective processes in steps S3 to S5 (S6). Wearable camera 10determines whether or not there is a default event (for example, anaction corresponding to action information defined in action table Atb1(which will be described later)) among behaviors of police officer 3 asa result of the determination in step S6 (S7). In a case where it isdetermined that there is no default event (for example, an actioncorresponding to action information defined in action table Atb1 (whichwill be described later)) among behaviors of police officer 3 (S7: NO),the process in wearable camera 10 returns to step S2.

On the other hand, in a case where it is determined that there is adefault event (for example, an action corresponding to actioninformation defined in action table Atb1 (which will be describedlater)) among behaviors of police officer 3 (S7: YES), wearable camera10 generates action index AL1 in which a detection time point of thedefault event is correlated with information regarding the default eventaccording to the determination in action information generator 19D. Asillustrated in FIG. 8, action index AL1 may indicate the whole ofdetection time points of a plurality of events detected in a time seriesand information regarding the events, and may indicate a detection timepoint of a single event and information regarding the event. Wearablecamera 10 records action index AL1 on recorder 15 in correlation withcaptured videos recorded on recorder 15 by video/sound data generator19A (S8). After step S8, the process in wearable camera 10 returns tostep S2.

Here, details of the determination process in step S6 will be describedwith reference to FIG. 7. FIG. 7 is an explanatory diagram illustratingrelationship examples among detected actions, various pieces of measureddata, and action table Atb1.

In step S6, action information generator 19D reads and acquires actiontable Atb1 from recorder 15. Action table Atb1 indicates, for example, acorrespondence relationship between various pieces of measured data usedto detect a default event (action) and the name of an actually detectedevent (action) when detection of the default event is determined. Actiontable Atb1 may be recorded on recorder 15, and may be recorded on memory13. Herein, the various pieces of measured data include accelerationdata measured by acceleration sensor AC, inclination data measured bygyro sensor GY, sound analysis result data generated by video/sound dataanalyzer 19C, video analysis result data generated by video/sound dataanalyzer 19C, and activity amount data measured by an activity meter(which will be described later).

Action information generator 19D refers to action table Atb1, anddetermines whether or not a behavior of police officer 3 was performedby using at least two types of measured data among the four types ofmeasured data acquired in the respective processes in steps S3 to S5.

For example, in a case where acceleration data and inclination data ofthe same extent as acceleration data (5,6,8) and inclination data(4,6,8) in the three-axis (the x axis, the y axis, and the z axis)directions of the orthogonal coordinate system are obtained, forexample, action information generator 19D determines that a defaultevent (action) “dangerous falling” occurred assuming that police officer3 fell backward.

For example, in a case where acceleration data and inclination data ofthe same extent as acceleration data (8,4,3) and inclination data(7,5,4) in the three-axis (the x axis, the y axis, and the z axis)directions of the orthogonal coordinate system are obtained, forexample, action information generator 19D determines that a defaultevent (action) “dash” occurred assuming that police officer 3 started torun.

For example, in a case where acceleration data and inclination data ofthe same extent as acceleration data (5,6,3) and inclination data(6,7,6) in the three-axis (the x axis, the y axis, and the z axis)directions of the orthogonal coordinate system are obtained, forexample, action information generator 19D determines that a defaultevent (action) “hit (falling)” occurred assuming that police officer 3fell frontward.

For example, in a case where acceleration data and inclination data ofthe same extent as acceleration data (6,3,4) and inclination data(2,3,4) in the three-axis (the x axis, the y axis, and the z axis)directions of the orthogonal coordinate system are obtained, forexample, action information generator 19D determines that a defaultevent (action) “jostling” occurred assuming that police officer 3 movedvertically.

For example, in a case where acceleration data and inclination data ofthe same extent as acceleration data (2,4,3) and inclination data(6,7,8) in the three-axis (the x axis, the y axis, and the z axis)directions of the orthogonal coordinate system are obtained, forexample, action information generator 19D determines that a defaultevent (action) “gun leveling” occurred assuming that police officer 3leveled the gun. The event “gun leveling” may be determined by referringto data measured by the sensor (not illustrated) attached to the holsteras described with reference to FIG. 5.

FIG. 8 is a diagram illustrating an example of action index AL1. Actionindex AL1 is a time-series behavior table of police officer 3,indicating an order of events (actions) over time of police officer 3detected by wearable camera 10, and a summary or the content of eachaction. FIG. 8 illustrates action index AL1 in which, with respect to atotal of eleven events (actions), detection time points of the events(actions), thumbnail images SM1 to SM11 corresponding to the detectiontime points of the respective actions, the pieces of content of therespective actions, and determination conditions of the respectiveactions are correlated with each other.

A detailed description will be made of action index AL1 in FIG. 8.First, in an index (a time point of 01:00:10 p.m.) of a first row,wearable camera 10 has determined that recording of captured videostypified by thumbnail image SM1 was started on the basis of pressing ofa REC button (that is, recording switch SW1) performed by police officer3 and reception of a trigger from the ICV (that is, reception of arecording starting instruction from in-car camera system 30).

Next, in an index (a time point of 01:20:32 p.m.) of a second row,wearable camera 10 has detected that the door of police vehicle 7 whichpolice officer 3 was aboard was opened, for example, on the basis of avideo analysis result, and has determined that police officer 3 arrivedat a site including a field by car (that is, police vehicle 7).

Thumbnail image SM2 is generated on the basis of a captured video at apoint where it was detected that police officer 3 arrived at the site,and indicates a situation of the site.

Next, in an index (a time point of 01:21:14 p.m.) of a third row,wearable camera 10 has detected that police officer 3 was continuouslymoving for a predetermined time or more on the basis of measured data ineach of acceleration sensor AC and gyro sensor GY, and has determinedthat police officer 3 walked and moved to the field. Thumbnail image SM3is generated on the basis of a captured video at a point at which it wasdetected that police officer 3 walked and moved to the field, andindicates a situation at a point at which police officer 3 was walkingto the field.

Next, in an index (a time point of 01:24:33 p.m.) of a fourth row,wearable camera 10 has detected that police officer 3 did not moved fora predetermined time or more on the basis of measured data in each ofacceleration sensor AC and gyro sensor GY, and has determined thatpolice officer arrived at the field. Thumbnail image SM4 is generated onthe basis of a captured video at a point at which it was detected thatpolice officer 3 arrived at the field, and indicates a situation of thefield.

Next, in an index (a time point of 01:26:45 p.m.) of a fifth row,wearable camera 10 has detected that police officer 3 was running on thebasis of measured data in each of acceleration sensor AC and gyro sensorGY, and has determined that police officer 3 was running in pursuit of acriminal. Thumbnail image SM5 is generated on the basis of a capturedvideo at a point at which it was detected that police officer 3 wasrunning in pursuit of the criminal, and indicates a situation ofpursuing the criminal.

Next, in an index (a time point of 01:30:33 p.m.) of a sixth row,wearable camera 10 has determined that police officer 3 took the gunfrom the holster and leveled the gun on the basis of data measured bythe sensor (not illustrated) attached to the holster and data indicatingmotion of the arms detected by the activity meter (which will bedescribed later) attached to the arm of police officer 3. Thumbnailimage SM6 is generated, for example, on the basis of a captured video ata point at which it was detected that police officer 3 leveled the gunat the criminal, and indicates a situation at a point at which policeofficer 3 faced the criminal.

Next, in an index (a time point of 01:30:34 p.m.) of a seventh row,wearable camera 10 has determined that police officer 3 said “freeze”and urged the criminal to stop on the basis of sound analysis resultdata. Thumbnail image SM7 is generated, for example, on the basis of acaptured video at a point at which it was detected that police officer 3urged the criminal to stop, and indicates a situation at a point atwhich police officer 3 faced the criminal.

Next, in an index (a time point of 01:30:40 p.m.) of an eighth row,wearable camera 10 has detected that police officer 3 was running on thebasis of measured data in each of acceleration sensor AC and gyro sensorGY, and has determined that police officer 3 was running in pursuit of acriminal. Thumbnail image SM8 is generated on the basis of a capturedvideo at a point at which it was detected that police officer 3 wasrunning in pursuit of the criminal, and indicates a situation ofpursuing the criminal.

Next, in an index (a time point of 01:31:05 p.m.) of a ninth row,wearable camera 10 has determined that police officer 3 took the gunfrom the holster and leveled the gun on the basis of data measured bythe sensor (not illustrated) attached to the holster and data indicatingmotion of the arms detected by an activity meter (which will bedescribed later) attached to the arm of police officer 3. Thumbnailimage SM9 is generated, for example, on the basis of a captured video ata point at which it was detected that police officer 3 leveled the gunat the criminal, and indicates a situation at a point at which policeofficer 3 faced the criminal.

Next, in an index (a time point of 01:31:05 p.m.) of a tenth row,wearable camera 10 has determined that police officer 3 said “freeze”and urged the criminal to stop on the basis of sound analysis resultdata. Thumbnail image SM10 is generated, for example, on the basis of acaptured video at a point at which it was detected that police officer 3urged the criminal to stop, and indicates a situation at a point atwhich police officer 3 faced the criminal.

Finally, in an index (a time point of 01:31:07 p.m.) of an eleventh row,wearable camera 10 has determined that police officer 3 shot the gun onthe basis of data regarding an analysis result of sounds (for example, avolume and a frequency) and data indicating motion of the arms detectedby the activity meter (which will be described later) attached to thearm of police officer 3. Thumbnail image SM11 is generated, for example,on the basis of a captured video at a point at which it was detectedthat police officer 3 shot the gun, and indicates a situation at a pointat which police officer 3 faced the criminal.

As mentioned above, wearable camera 10 of the present exemplaryembodiment generates action index AL1 illustrated in FIG. 8 and recordsaction index AL1 on recorder 15. Therefore, time-series behaviors(actions) detected during business of police officer 3 can be understoodin detail, and, thus, for example, police officer 3 can provejustification of the behaviors to an opponent (for example, a superiorofficer of police officer 3, an executive of police department PD, or athird party). Particularly, in a case where a suspect or a criminal inpursuit wad dead, justification of a behavior (for example, using thegun) of police officer 3 may be required to be shown by an evidence. Forexample, an explanation or a report on detailed information such as amap of a field, pictures of the field, and the number of times of urginga suspect or a criminal to stop is required. Thus, it is necessary tocreate a report for explaining behaviors of police officer 3 in pursuitin detail and objectively. According to wearable camera 10 of thepresent exemplary embodiment, action index AL1 is attached as anappendix of the case report, and thus it is possible to efficientlycreate the case report.

FIG. 9 is a diagram illustrating an example of action map MP1 in whichinformation regarding positions where actions are detected in a timeseries is displayed to be superimposed on map data MP0. Action map MP1is generated to correspond to action index AL1 illustrated in FIG. 8.

Action map MP1 in FIG. 9 will be described in detail. [1] in action mapMP1 indicates position information of wearable camera 10 correspondingto the detection time point in the index of the first row of actionindex AL1 in FIG. 8. Hereinafter, similarly, [2], [3], [4], [5], [6],[7], [8], [9], [10], and [11] in action map MP1 respectively indicateposition information of wearable camera 10 corresponding to thedetection time points in the indexes of the second row, the third row,the fourth row, the fifth row, the sixth row, the seventh row, theeighth row, the ninth row, the tenth row, and the eleventh row of actionindex AL1 in FIG. 8. In action map MP1, trajectory TRC1 connecting thepositions where the respective events (actions) in action index AL1 weredetected is also displayed. Trajectory TRC1 is generated by actioninformation generator 19D to which position information from GPSreceptor 18 is input at any time.

According to action map MP1, wearable camera 10 can generate map data inwhich respective pieces of position information of when a series ofbehaviors (actions) of police officer 3 in a time series correspondingto action index AL1 can be intuitively understood in detail incomparison with map data MP0. Police officer 3 viewing action map MP1can also check, for example, an escape route of a suspect or a criminalin pursuit, and can thus find the tendency in escape of the suspect orthe criminal.

FIG. 10 is a flowchart illustrating a detailed example of an operationprocedure for generation of action index AL1 or recording of capturedvideos in wearable camera 10 of Exemplary Embodiment 1. In descriptionof FIG. 10, the same content as that of the description of FIG. 6 willbe made briefly or omitted, and different content will be described. Inthe same manner as in FIG. 6, FIG. 10 will be described assuming thatthe power source of wearable camera 10 is in an ON state.

In FIG. 10, after step S1, wearable camera 10 determines whether or notdata regarding captured videos obtained in step S1 is being recorded(S2). In a case where the data is not being recorded (S2: NO), theprocess in wearable camera 10 proceeds to step S9.

In other words, in wearable camera 10, processor 19 acquiresacceleration data and inclination data in the three-axis directions ofthe orthogonal coordinate system measured by acceleration sensor AC andgyro sensor GY (S9).

In wearable camera 10, action information generator 19D acquires dataregarding a sound analysis result delivered from video/sound dataanalyzer 19C (S10). In wearable camera 10, action information generator19D acquires data regarding a video analysis result delivered fromvideo/sound data analyzer 19C (S11). An order of the processes in stepsS9 to S11 may be any order.

In wearable camera 10, action information generator 19D refers to actiontable Atb1 (refer to FIG. 7), and determines an action of police officer3 by using at least two types of measured data among the four types ofmeasured data (that is, the acceleration data and the inclination datain the three-axis directions of the orthogonal coordinate system, thesound analysis result data, and the video analysis result data) acquiredin the respective processes in steps S3 to S5 (S12). Wearable camera 10determines whether or not there is a default event (for example, anaction corresponding to action information defined in action table Atb1)among behaviors of police officer 3 as a result of the determination instep S12 (S13). In a case where it is determined that there is nodefault event (for example, an action corresponding to actioninformation defined in action table Atb1) among behaviors of policeofficer 3 (S13: NO), the process in wearable camera 10 returns to stepS2.

On the other hand, in a case where it is determined that there is adefault event (for example, an action corresponding to actioninformation defined in action table Atb1) among behaviors of policeofficer 3 (S13: YES), wearable camera 10 starts to record capturedvideos obtained in step S1 on recorder 15 according to the determinationin action information generator 19D (S14). After step S14, the processin wearable camera 10 returns to step S2. Consequently, for example,even in a case where police officer 3 does not independently operaterecording switch SW1, or even in a case of a situation in which it ishard for police officer 3 to independently operate recording switch SW1,wearable camera 10 can prevent omission of recording of captured videosof a subject on the front side of police officer 3, and can thusappropriately store evidence videos during business of police officer 3.

As mentioned above, wearable camera 10 of the present exemplaryembodiment can be worn or carried by police officer 3, records capturedvideos of a subject on the front side of police officer 3 on recorder15, and acquires information (for example, acceleration data orinclination data in the three-axis directions of the orthogonalcoordinate system) regarding motion of police officer 3. Wearable camera10 determines whether or not at least one default event (for example,the actions illustrated in FIG. 5) has occurred on the basis of theinformation regarding motion of police officer 3 acquired (specifically,measured) during recording of captured videos of the subject. Wearablecamera 10 generates event list information (for example, action indexAL1) in which a detection time point of the default event is correlatedwith information regarding the default event according to determinationthat at least one default event (for example, the actions illustrated inFIG. 5) has occurred during recording of captured videos of the subject,and records the event list information on recorder 15 in correlationwith the captured videos of the subject.

Consequently, even if police officer 3 does not independently reproduceand watch captured videos recorded during business of police officer 3afterward, wearable camera 10 can determine each of various behaviors ofpolice officer 3 performed in a time series from captured videosrecorded by wearable camera 10 and can record the determined behaviorsas information. Therefore, police officer 3 attaches, for example,action index AL1 to an appendix material of a case report in whichdetails of behaviors of police officer 3 performed in a time seriesduring business are collected, and can thus considerably reduce creationman-hours of the case report. In other words, wearable camera 10 canrecord action index AL1 and can thus efficiently support business ofpolice officer 3.

Wearable camera 10 generates a thumbnail image corresponding to adetection time point of at least one default event (for example, theactions illustrated in FIG. 5) by using a captured video of a subject,and records action index AL1 including the generated thumbnail image onrecorder 15. Consequently, wearable camera 10 enables a person viewing ascreen on which action index AL1 is output and displayed to accuratelyunderstand general situations of a subject at detection time points ofbehaviors (actions) of police officer 3 in a time series.

Wearable camera 10 acquires position information of the wearable camerain GPS receptor 18. Wearable camera 10 acquires position information ofwearable camera 10 corresponding to a detection time point of at leastone default event, generates action map MP1 (event map information) inwhich the acquired position information is superimposed on map data MP0,and records action map MP1 on recorder 15. Consequently, wearable camera10 can generate map data in which respective pieces of positioninformation of when a series of behaviors (actions) of police officer 3in a time series corresponding to action index AL1 can be intuitivelyunderstood in detail in comparison with map data MP0.

Wearable camera 10 collects sounds around police officer 3 in microphone29A. Wearable camera 10 determines whether or not at least one defaultevent occurred on the basis of information (for example, accelerationdata or inclination data in the three-axis directions of the orthogonalcoordinate system) regarding motion of police officer 3 acquired(specifically, measured) during recording of captured videos of asubject and sounds collected by microphone 29A. Consequently, wearablecamera 10 can accurately detect a behavior (a behavior of urging asuspect or a criminal in pursuit to stop) which is hard to detect on thebasis of only information regarding motion of police officer 3, and canthus leave (store) a justifiable behavior as action index AL1.

Next, a description will be made of an example in which action index AL1is generated on the basis of cooperation between wearable camera 10 andback end server 50.

FIG. 11 is a block diagram illustrating a detailed example of aninternal configuration of back end server 50 of Exemplary Embodiment 1.Back end server 50 (server apparatus) includes CPU 51, I/O controller52, communicator 53, memory 54, input 55, display 56, speaker 59,storage controller 57, and storage 58.

CPU 51 functions as a controller of back end server 50, performs acontrol process of integrating operations of the respective constituentelements of back end server 50 as a whole, a process of transmitting andreceiving data to and from the respective constituent elements of backend server 50, a data calculation (computation) process, and a datastorage process. CPU 51 is operated according to a program and datastored in memory 54. CPU 51 uses memory 54 during an operation thereof.Although not illustrated in FIG. 11, CPU 51 includes the sameconfiguration as action information generator 19D of processor 19illustrated in FIG. 4. In other words, CPU 51 can perform the sameoperation as that of action information generator 19D.

I/O controller 52 performs control on input and output of data betweenCPU 51 and the respective constituent elements (for example,communicator 53, input 55, display 56, and storage controller 57) ofback end server 50, and relays data from CPU 51 and data to CPU 51. I/Ocontroller 52 may be formed integrally with CPU 51.

Communicator 53 performs wired or wireless communication with, forexample, in-car recorder 33, in-car PC 32, smart phone 40, wearablecamera 10 which can be worn or held by police officer 3, back endstreaming server 60, or back end clients 70 a and 70 b.

Memory 54 is formed by using, for example, a RAM, a ROM, and anonvolatile or volatile semiconductor memory, functions as a work memoryduring an operation of CPU 51, and stores a predetermined program anddata for operating CPU 51. The same data of action table Atb1 as actiontable Atb1 (refer to FIG. 7) stored in memory 13 or recorder 15 ofwearable camera 10 is recorded on memory 54.

Input 55 is a user interface (UI) which receives an input operationperformed by police officer 3 or a person in charge in police departmentPD, and notifies CPU 51 of the input operation via I/O controller 52,and is a pointing device such as a mouse or a keyboard. Input 55 may beformed by using a touch panel or a touch pad which is disposed tocorrespond to, for example, a screen of display 56, and in which anoperation can be performed with the finger of a person in charge or astylus pen. Back end server 50 may be operated from back end clients 70a and 70 b connected thereto via a network in police department PD.

Display 56 (monitor) is formed by using, for example, a liquid crystaldisplay (LCD) or an organic EL display, and displays various pieces ofinformation. For example, in a case where videos captured or recorded bywearable camera 10 are input according to an input operation performedby police officer 3 or a person in charge, display 56 displays thevideos on a screen under an instruction of CPU 51. For example, in acase where videos captured or recorded by in-car cameras 31 are inputaccording to an input operation performed by police officer 3 or aperson in charge, display 56 displays the videos on a screen under aninstruction of CPU 51. In a case where an operation is performed fromback end clients 70 a and 70 b connected to display 56 via the networkin police department PD, various pieces of information are displayed onback end clients 70 a and 70 b.

For example, in a case where sounds collected by wearable camera 10 areinput according to an input operation performed by police officer 3 or aperson in charge, speaker 59 outputs the sounds under an instruction ofCPU 51. In a case where an operation is performed from back end clients70 a and 70 b connected to speaker 59 via the network in policedepartment PD, sounds are output to speakers connected to back endclients 70 a and 70 b.

In a case where CPU 51 requests back end streaming server 60 to transmitaccumulated captured video data, storage controller 57 controls anoperation of storing received video data in storage 58 in response tothe request. Storage 58 is a storage device such as a solid state drive(SSD) or a hard disk drive (HDD) controlled by storage controller 57,and accumulates captured video data transmitted from wearable camera 10via I/O controller 52 in response to an instruction from CPU 51.

FIG. 12 is a sequence drawing illustrating a detailed example of ageneration operation procedure for action index ALL based on cooperationbetween wearable camera 10 and back end server 50 in ExemplaryEmbodiment 1. In description of FIG. 12, the same content as that of thedescription of FIG. 6 will be made briefly or omitted, and differentcontent will be described. FIG. 12 will be described assuming thatwearable camera 10 and back end server 50 are connected to each other soas to perform communication via a wireless LAN.

In FIG. 12, after step S5, wearable camera 10 transmits a determinationrequest including the four types of measured data (that is, theacceleration data and the inclination data in the three-axis directionsof the orthogonal coordinate system, the sound analysis result data, andthe video analysis result data) acquired in the respective processes insteps S3 to S5, to back end server 50 (S25).

In step S25, back end server 50 receives the determination requestincluding the four types of measured data (that is, the accelerationdata and the inclination data in the three-axis directions of theorthogonal coordinate system, the sound analysis result data, and thevideo analysis result data) transmitted from wearable camera 10. In backend server 50, CPU 51 refers to action table Atb1 (refer to FIG. 7)recorded on memory 54, and determines an action of police officer 3 byusing at least two types of measured data among the four types ofmeasured data (that is, the acceleration data and the inclination datain the three-axis directions of the orthogonal coordinate system, thesound analysis result data, and the video analysis result data) receivedin step S25 (S26).

Back end server 50 determines whether or not there is a default event(for example, an action corresponding to action information defined inaction table Atb1) among behaviors of police officer 3 as a result ofthe determination in step S26 (S27). In a case where it is determinedthat there is no default event (for example, an action corresponding toaction information defined in action table Atb1) among behaviors ofpolice officer 3 (S27: NO), back end server 50 transmits a responseindicating that there is no action information defined in action tableAtb1 to wearable camera 10 (S28). In a case where the responsetransmitted from back end server 50 is received in step S28, wearablecamera 10 performs the processes from step S3 again. In other words,wearable camera 10 is in a waiting state until a write instruction isreceived from back end server 50 in step S30 which will be describedlater, and repeatedly performs the processes from step S3.

On the other hand, in a case where it is determined that there is adefault event (for example, an action corresponding to actioninformation defined in action table Atb1) among behaviors of policeofficer 3 (S27: YES), back end server 50 generates a write instructionfor writing action index AL1 in which a detection time point of thedefault event is correlated with information regarding the default eventaccording to the determination in CPU 51 (S29). Back end server 50transmits the write instruction generated in step S29 to wearable camera10 (S30). In a case where the write instruction transmitted from backend server 50 in step S30 is received, wearable camera 10 generatesaction index AL1 in which a detection time point of the default eventdetected by back end server 50 is correlated with information regardingthe default event on the basis of the write instruction, and recordsaction index AL1 on recorder 15 (S8A). After step S8A, the process inwearable camera 10 returns to step S3, and the processes from step S3are repeatedly performed.

As mentioned above, according to cooperation between wearable camera 10and back end server 50 in wearable camera system 1000 of the presentexemplary embodiment, wearable camera 10 records captured videos of asubject on the front side of police officer 3 on recorder 15, acquiresinformation regarding motion of police officer 3 during recording of thecaptured videos of the subject, and transmits the acquired informationregarding motion of police officer 3 to back end server 50. Back endserver 50 receives the information regarding motion of police officer 3transmitted from wearable camera 10, and determines whether or not atleast one default event has occurred on the basis of the receivedinformation regarding motion of police officer 3. Back end server 50transmits a write instruction (generation instruction) for action indexAL1 in which a detection time point of the default event is correlatedwith information regarding the default event to the wearable camera 10according to determination that at least one default event has occurred.Wearable camera 10 receives the write instruction for action index AL1transmitted from back end server 50, generates action index AL1 inresponse to the write instruction, and records action index AL1 onrecorder 15 in correlation with the captured videos of the subject.

Consequently, in wearable camera system 1000, even if police officer 3does not independently reproduce and watch captured videos recordedduring business of police officer 3 afterward, back end server 50 canhighly accurately determine each of various behaviors of police officer3 performed in a time series from captured videos recorded by wearablecamera 10 and can record the determined behaviors in wearable camera 10as information. Therefore, police officer 3 attaches, for example,action index AL1 to an appendix material of a case report in whichdetails of behaviors of police officer 3 performed in a time seriesduring business are collected, and can thus considerably reduce creationman-hours of the case report. In other words, wearable camera 10 canrecord action index AL1 and can thus efficiently support business ofpolice officer 3. Back end server 50 determines a behavior of policeofficer 3 by using at least two types of measured data among the fourtypes of measured data (that is, the acceleration data and theinclination data in the three-axis directions of the orthogonalcoordinate system, the sound analysis result data, and the videoanalysis result data). Therefore, the configuration of actioninformation generator 19D can be omitted in processor 19 of wearablecamera 10, so that a configuration of wearable camera 10 can besimplified, and thus an increase in cost can be suppressed.

In wearable camera system 1000, wearable camera 10 may transmit capturedvideos recorded on recorder 15 and action index AL1 correlated with eachother to back end server 50. Back end server 50 receives the capturedvideos recorded on recorder 15 and action index AL1 transmitted fromwearable camera 10, and records the captured videos recorded on recorder15 and action index AL1 on storage 58 (second recorder) in correlationwith each other. Consequently, in wearable camera system 1000, actionindex AL1 generated by wearable camera 10 can be stored in back endserver 50, and action index AL1 generated by wearable camera 10 can bebacked up. Since back end server 50 can register (accumulate) actionindex AL1 in correlation with identification information of wearablecamera 10, a person in police department PD can integrally manage actionindex AL1 for each wearable camera 10 or action index AL1 stored instorage 58, and can thus provide a function of retrieving a capturedvideo related to a behavior (action) of police officer 3 which will bedescribed later.

Next, a description will be made of an example in which action index AL1is generated on the basis of cooperation between wearable camera 10 andactivity meter 200 as an external sensor. Activity meter 200 is attachedto a part of the body of police officer 3 (user) and is used, andacquires information regarding an activity amount of police officer 3.The information regarding an activity amount of police officer 3 is, forexample, biological information typified by information regarding motionof police officer 3, a body temperature, and a heart rate.

FIG. 13A is a diagram illustrating an example in which wearable camera10 and activity meter 200 perform direct short-range radio communicationwith each other in wearable camera system 1000. FIG. 13B is a diagramillustrating an example in which wearable camera 10 and activity meter200 perform short-range radio communication with each other via smartphone 40 in wearable camera system 1000.

Wearable camera system 1000 in FIG. 13A is configured to includewearable camera 10 and activity meter 200. Activity meter 200 includessensors acquiring various pieces of information (activity amountinformation) regarding human activities such as motion, a heart rate, aperspiration, a body temperature, and the like of police officer 3.Activity meter 200 is mounted on, for example, a user's wrist, andmeasures an activity amount. Details of activity meter 200 will bedescribed later. Wearable camera 10 and activity meter 200 performcommunication with each other, and transmit and receive informationacquired in activity meter 200. Communication between wearable camera 10and activity meter 200 may employ, for example, either one of BLEcommunication and wireless LAN communication.

Wearable camera system 1000 in FIG. 13B is configured to includewearable camera 10, activity meter 200, and smart phone 40. Smart phone40 can perform communication with wearable camera 10 and activity meter200, and wearable camera 10 and activity meter 200 perform communicationwith each other via smart phone 40, and transmit and receive informationacquired in activity meter 200. Communication between wearable camera10, smart phone 40, and activity meter 200 may employ, for example,either one of BLE communication and wireless LAN communication.

FIG. 14 is a block diagram illustrating a detailed example of aninternal configuration of activity meter 200. Activity meter 200includes calculator 201, storage 202, display 203, power source 204,communicator 205, antenna 206, and vibrator 207. Activity meter 200includes gyro sensor 211, acceleration sensor 212, heart rate sensor213, perspiration sensor 214, and temperature sensor 215 as externalsensors measuring an activity amount of police officer 3. Activity meter200 may include at least one of the above-described various sensors.Activity meter 200 includes operation switch 221, communication switch222, and reset switch 223.

Calculator 201 has a processing device such as a microprocessor, andperforms a calculation process of a measured value on the basis of anoutput signal indicating a predetermined physical quantity, output froma sensor. Calculator 201 calculates an activity amount such as a defaultaction, a heart rate, a perspiration, or a body temperature of policeofficer 3 (user) on the basis of the measured value acquired from thesensor. Storage 202 is formed of, for example, a semiconductor memorysuch as a flash ROM, and stores a program for operating calculator 201,and acquired data such as a measured value or an activity amount.Display 203 is formed of, for example, a display device such as an LEDor an LCD, and displays an operation state of activity meter 200, anacquired activity amount, and the like with brightness and darkness oflight, text, images, and the like. Power source 204 is formed of, forexample, a rechargeable secondary battery, and supplies source power tothe respective constituent elements of activity meter 200.

Communicator 205 includes, for example, a communication circuitperforming wireless communication such as BLE communication, andtransmits and receives information regarding an activity amount to andfrom wearable camera 10 or wearable camera 10 and smart phone 40.Antenna 206 transmits and receives radio signals during communicationusing communicator 205. Vibrator 207 vibrates at a predetermined timingon the basis of an instruction from calculator 201, and sends anotification to police officer 3 (user).

Gyro sensor 211 measures angular velocities in the three-axis directionsof the orthogonal coordinate system of activity meter 200. Accelerationsensor 212 measures accelerations in the three-axis directions of theorthogonal coordinate system of activity meter 200. Calculator 201calculates activity amount information regarding an action of a user(for example, police officer 3) wearing activity meter 200 on the basisof outputs from gyro sensor 211 and acceleration sensor 212. Heart ratesensor 213 has, for example, a light emitting element and a lightreceiving element, and measures a heart rate of a user (for example,police officer 3) wearing activity meter 200 by irradiating bloodvessels in a human body with light, receiving reflected light thereof,and measuring pulses on the basis of a change in an amount of receivedlight. Calculator 201 calculates activity amount information regarding aheart rate on the basis of outputs from heart rate sensor 213.Perspiration sensor 214 measures a perspiration of a user (for example,police officer 3) wearing activity meter 200, for example, on the basisof humidity or the like around a skin. Calculator 201 calculatesactivity amount information regarding a perspiration such as thepresence or absence of a perspiration or a perspiration amount on thebasis of outputs from heart rate sensor 213. Temperature sensor 215measures a body temperature of a user (for example, police officer 3)wearing activity meter 200. Calculator 201 calculates activity amountinformation regarding a body temperature such as a body temperatureincrease.

Operation switch 221 is, for example, a pressing type button switch forinputting an operation instruction such as switching of the displaycontent of activity meter 200 and switching of an operation mode.Communication switch 222 is, for example, a pressing type button switchfor inputting a communication instruction such as communication startingor communication stopping. Reset switch 223 is, for example, a pressingtype button switch for inputting a reset instruction in order to resetan acquired measured in activity meter 200 or to reset various settingsof activity meter 200.

FIG. 15 is a diagram illustrating an example of another action tableAtb2 regarding detected actions. In the same manner as in action tableAtb0 illustrated in FIG. 5, in action table Atb2, for example, thecontent of each default event (for example, an action) stored in memory13 or recorder 15 is correlated with a sensor used for detection of eachdefault event (for example, an action), or a detection condition. InFIG. 15, “extreme tension”, “increase/decrease in a heart rate”, a“perspiration”, and a “body temperature” which can be detected inrelation to measured data in activity meter 200 are added to the contentof action table Atb0 illustrated in FIG. 5. The same content as that ofthe description of FIG. 5 will be omitted, and different content will bedescribed.

For example, in a case where it is detected whether or not policeofficer 3 is in a state of extreme tension as an action, one or both ofpieces of data measured by heart rate sensor 213 and perspiration sensor214 of activity meter 200 are referred to.

For example, in a case where it is detected whether or not a heart rateof police officer 3 increases or decreases as an action, data measuredby heart rate sensor 213 of activity meter 200 is referred to.

For example, in a case where it is detected whether or not policeofficer 3 perspires as an action, data measured by perspiration sensor214 of activity meter 200 is referred to.

For example, in a case where it is detected whether or not a bodytemperature of police officer 3 increases or decreases as an action,data measured by temperature sensor 215 of activity meter 200 isreferred to.

FIG. 16 is a flowchart illustrating another detailed example of ageneration operation procedure for action index AL1 in wearable camera10 of Exemplary Embodiment 1. In description of FIG. 16, the samecontent as that of the description of FIG. 6 will be made briefly oromitted, and different content will be described. FIG. 16 will bedescribed assuming that the power sources of wearable camera 10 andactivity meter 200 are in an ON state.

In FIG. 16, after step S5, wearable camera 10 receives and acquiresmeasured data transmitted from activity meter 200 attached to a part ofthe body of police officer 3 (user) (S5A). An order of the processes insteps S3 to S5 and S5A may be any order. In wearable camera 10, afterstep S5A, action information generator 19D refers to action table Atb1(refer to FIG. 7), and determines an action of police officer 3 by usingat least two types of measured data among the five types of measureddata (that is, the acceleration data and the inclination data in thethree-axis directions of the orthogonal coordinate system, the soundanalysis result data, the video analysis result data, and the measureddata in activity meter 200) acquired in the respective processes insteps S3 to S5 and S5A (S6A). The processes from step S6A are the sameas those in FIG. 6, and thus description thereof will be omitted.

FIG. 17 is a flowchart illustrating another detailed example of anoperation procedure for generation of action index AL1 or recording ofcaptured videos in wearable camera 10 of Exemplary Embodiment 1. Indescription of FIG. 17, the same content as that of the description ofFIG. 10 will be made briefly or omitted, and different content will bedescribed. In the same manner as in FIG. 10, FIG. 17 will be describedassuming that the power sources of wearable camera 10 and activity meter200 are in an ON state.

In FIG. 17, after step S5, wearable camera 10 receives and acquiresmeasured data transmitted from activity meter 200 attached to a part ofthe body of police officer 3 (user) (S5A). An order of the processes insteps S3 to S5 and S5A may be any order. In wearable camera 10, afterstep S5A, action information generator 19D refers to action table Atb1(refer to FIG. 7), and determines an action of police officer 3 by usingat least two types of measured data among the five types of measureddata (that is, the acceleration data and the inclination data in thethree-axis directions of the orthogonal coordinate system, the soundanalysis result data, the video analysis result data, and the measureddata in activity meter 200) acquired in the respective processes insteps S3 to S5 and S5A (S6A). The processes from step S6A are the sameas those in FIG. 10, and thus description thereof will be omitted.

After step S11, wearable camera 10 receives and acquires measured datatransmitted from activity meter 200 attached to a part of the body ofpolice officer 3 (user) (S11A). An order of the processes in steps S9 toS11 and S11A may be any order. In wearable camera 10, after step S11A,action information generator 19D refers to action table Atb1 (refer toFIG. 7), and determines an action of police officer 3 by using at leasttwo types of measured data among the five types of measured data (thatis, the acceleration data and the inclination data in the three-axisdirections of the orthogonal coordinate system, the sound analysisresult data, the video analysis result data, and the measured data inactivity meter 200) acquired in the respective processes in steps S9 toS11 and S11A (S12A). The processes from step S12A are the same as thosein FIG. 10, and thus description thereof will be omitted.

Consequently, for example, even in a case where police officer 3 doesnot independently operate recording switch SW1, or even in a case of asituation in which it is hard for police officer 3 to independentlyoperate recording switch SW1, wearable camera 10 can prevent omission ofrecording of captured videos of a subject on the front side of policeofficer 3 by taking into consideration measured data in activity meter200, and can thus appropriately store evidence videos during business ofpolice officer 3.

As mentioned above, in wearable camera 10 of the present exemplaryembodiment, BLE communicator 21A or WLAN communicator 21B performscommunication with activity meter 200 (external sensor) acquiringinformation regarding an activity amount of police officer 3 (user).Wearable camera 10 determines whether or not at least one default eventhas occurred on the basis of the information regarding motion of policeofficer 3 acquired (specifically, measured) during recording of capturedvideos of a subject and information regarding an activity amount ofpolice officer 3 received from activity meter 200.

Consequently, wearable camera 10 can accurately determine the presenceor absence of a symptom indicating a certain abnormal change in the bodyof police officer 3 in addition to actions of police officer 3 performedduring business, and can thus generate action index AL1 finelyindicating behaviors of police officer 3 performed in a time series orgenerated symptoms during business.

Next, a description will be made of an operation example after actionindex AL1 and captured videos generated by different wearable cameras 10are recorded on back end server 50 of police department PD for backup.Here, a case is assumed in which, for example, a professional in policedepartment PD who is different from police officer 3 who has been to acase field checks an evidence video attached to documents submitted toan institution such as a court or a public prosecutor's office, theprofessional retrieves and watches videos related to necessary behaviorsduring business of police officer 3. However, an operation example isnot limited to the above-described assumed example.

FIG. 18 is a diagram illustrating an example of retrieval result screenWD1 displaying an entry field for an action information retrievalcondition and a retrieval result. Retrieval result screen WD1illustrated in FIG. 18 is an example of a screen displayed on display 56as a processing result in a dedicated application (for example, aretrieval application (specifically, CPU 51) for action index AL1) whichis installed in advance to be executable in back end server 50.

Retrieval result screen WD1 illustrated in FIG. 18 includes date andtime entry field IP1, action information entry field IP2, retrievalbutton SC1, and retrieval result list OP1. The date and time which is aretrieval target is entered into date and time entry field IP1 throughan operation performed by a user (for example, the above-describedprofessional) in the retrieval application for action index AL1. Actioninformation which is a retrieval target is entered into actioninformation entry field IP2 through an operation performed by a user(for example, the above-described professional) in the retrievalapplication for action index AL1. In the example illustrated in FIG. 18,“pursuit” is entered as action information. In other words, action indexAL1 is retrieved in which it is determined (detected) that policeofficer 3 wearing or holding wearable camera 10 has performed “pursuit”as a behavior during business. In a case where retrieval button SC1 ispressed, the retrieval application (specifically, CPU 51) for actionindex AL1 refers to storage 58 on which action index AL1 and capturedvideo data are recorded in correlation with each other, and retrievesaction index AL1 in which it is determined (detected) that policeofficer 3 wearing or holding wearable camera 10 has performed “pursuit”as a behavior during business.

For example, extracted records RC1, RC2, RC3, RC4, and RC5 of fiveaction indexes are displayed in retrieval result list OP1. In each ofrecords RC1 to RC5, a file name of captured video data, a thumbnailimage, the date and time (not illustrated in FIG. 18), informationregarding an imaging person (that is, a police officer wearing orholding wearable camera 10), and a reproduction button for the capturedvideo data are correlated with each other. In a case where there is aretrieval target action or symptom (refer to FIG. 15) in captured videoscorresponding to a file name, a thumbnail image is an image (forexample, a still image, or a moving image in an animation form)generated on the basis of a captured video of when the action or thesymptom was detected. In a case where there is no retrieval targetaction or symptom (refer to FIG. 15) in captured videos corresponding toa file name, a thumbnail image is, for example, a thumbnail imagegenerated on the basis of a captured video at a point at which an actionor a symptom was initially detected.

According to record RC1 of retrieval result list OP1, in captured videodata with the file name “A.mp4”, thumbnail image SM21 at a point atwhich the behavior “pursuit” was detected is displayed, and it can beseen that a wearer (police officer) of wearable camera 10 at that timeis A.

Similarly, according to record RC2 of retrieval result list OP1, incaptured video data with the file name “B.mp4”, thumbnail image SM22 ata point at which the behavior “pursuit” was detected is displayed, andit can be seen that a wearer (police officer) of wearable camera 10 atthat time is B.

Similarly, according to record RC3 of retrieval result list OP1, incaptured video data with the file name “c.mp4”, thumbnail image SM23 ata point at which the behavior “pursuit” was detected is displayed, andit can be seen that a wearer (police officer) of wearable camera 10 atthat time is A.

FIG. 19 is an explanatory diagram illustrating an example in whichwatching screen WD2 for a captured video is displayed on the basis ofpressing of reproduction button RP1 corresponding to a certain record.Watching screen WD2 illustrated in FIG. 19 is displayed on display 56 bythe retrieval application (specifically, CPU 51) for action index AL1 asa result of pressing reproduction button RP1 corresponding to a certainrecord (for example, record RC1) in retrieval result screen WD1illustrated in FIG. 18.

Watching screen WD2 illustrated in FIG. 19 includes watching regionSWD1, reproduction button RP2, pause button TH1, seek bar SKB1, markerMK1, and one or more detection markers (a total of five detectionmarkers SP1, SP2, SP3, SP4, and SP5 in the example illustrated in FIG.19). Moving images of a pressing target captured video are reproduced inwatching region SWD1 by a dedicated application (for example, a watchingapplication (specifically, CPU 51) for a video or the like) installed inadvance in back end server 50 on the basis of pressing of reproductionbutton RP1 in retrieval result screen WD1. Reproduction button RP2 isused to control reproduction of moving images in watching region SWD1 inthe watching application. Pause button TH1 is used to control pause ofreproduction of moving images in watching region SWD1 in the watchingapplication. Seek bar SKB1 indicates a reproduction situation of movingimages in watching region SWD1. Marker MK1 indicates a reproductionpoint of moving images in watching region SWD1. Detection markers SP1 toSP5 indicate points at which an action or a symptom (refer to FIG. 15)was detected in a recording period of captured videos corresponding tothe moving images.

Watching screen WD2 illustrated in FIG. 19 includes correlation tableDT1 in which a reproduction time (reproduction time point) correspondingto each detection time point of actions or symptoms (refer to FIG. 15)detected in a period in which captured videos in watching region SWD1were recorded by wearable camera 10 is correlated with each piece ofaction information. In the following description, a correlation table(for example, correlation table DT1) is assumed to be generated by backend server 50 or back end clients 70 on the basis of action index AL1(event list information) generated by wearable camera 10, and is anexample of the event list information in the same manner as action indexAL1. Consequently, a user (for example, the above-describedprofessional) viewing watching screen WD2 can easily and directly graspa captured video of when an action or a symptom which the user isconcerned about was detected in watching region SWD1 in addition to anaction or a symptom (refer to FIG. 15) desired to be checked by theuser, and thus it is possible to considerably increase work efficiencyof a professional.

As mentioned above, in wearable camera system 1000 of the presentexemplary embodiment, back end server 50 extracts at least one capturedvideo in which a default event which is a retrieval operation target isdetected from storage 58 (second recorder) in response to a retrievaloperation for information regarding a default event (for example, anaction or a symptom), and displays retrieval result screen WD1 on whichthumbnail images SM21, SM22 and SM23 corresponding to the extractedcaptured videos are displayed, on display 56. Consequently, a user ofback end server 50 can easily grasp general situations in which anaction or a symptom desired to be examined by the user was detectedusing the thumbnail image, and thus it is possible to improve workefficiency of the user.

Back end server 50 displays retrieval result screen WD1 includingreproduction button RP1 for at least one extracted captured video ondisplay 56, and displays watching screen WD2 for a captured video whichis a designation operation target on display 56 in response to adesignation operation using reproduction button RP1. Consequently, auser of back end server 50 can easily watch the whole content ofcaptured videos of which details are desired to be checked by the useron watching screen WD2 on the basis of, for example, thumbnail images,and thus it is possible to improve convenience. Back end server 50displays watching screen WD2 including detection markers SP1, SP2, SP3,SP4 and SP5 (second reproduction buttons) corresponding to areproduction button (second reproduction button) for a captured videocorresponding to a detection time point of at least one event (forexample, an action or a symptom) detected from a captured video which isa designation operation target, on display 56. In a case where it isdetected that any detection marker (for example, detection marker SP1)has been designated, and reproduction button RP1 has been pressed, backend server 50 reads and reproduces captured video data at a time point(in other words, a time point at which action information “ran” incorrelation table DT1 was detected) of designated detection marker SP1.Consequently, a user of back end server 50 can easily switch to andwatch moving images regarding an action or a system detected from movingimages reproduced in watching screen WD2, and can thus smoothly performwork of checking, for example, an action index and a moving image.

Modification Example of Exemplary Embodiment 1

Next, as a modification example of Exemplary Embodiment 1, a descriptionwill be made of an example in which action table Atb1 a recorded on backend server 50 is updated on the basis of a rewriting operation performedby a user of back end client 70 a (which may also be back end client 70b), and thus back end server 50 learns measured data used for detectionof an action or a symptom which is a target of the rewriting operation.

Since a configuration of a wearable camera system of the modificationexample of Exemplary Embodiment 1 is the same as the configuration ofwearable camera system 1000 of Exemplary Embodiment 1, description ofthe same content will be omitted by referring to the same referencenumeral, and different from content will be described.

FIG. 20 is an explanatory diagram illustrating an example in whichlearning of measured data is started on the basis of rewriting of anaction information name in action table Atb1 a. In FIG. 20, action tableAtb1 a is an action table recorded on storage 58 before a rewritingoperation performed by a user of back end client 70 a. Action table Atb1b is an action table recorded on storage 58 after a rewriting operationperformed by the user of back end client 70 a.

FIG. 21 is a sequence diagram illustrating a detailed example of anoperation procedure regarding learning of measured data and update of alearning result, based on cooperation among wearable camera 10, back endserver 50, and back end client 70 a in the modification example ofExemplary Embodiment 1;

In FIGS. 20 and 21, it is assumed that the user of back end client 70 aperforms a rewriting operation, and thus the action information name“jostled” in action table Atb1 a recorded on storage 58 of back endserver 50 is rewritten into “pulled the gun” (S31). Back end client 70 atransmits an instruction for starting learning of various pieces ofmeasured data used to detect the designated new action “pulled the gun”to back end server 50 in response to the rewriting operation in step S31(S32).

In a case where the instruction transmitted from back end client 70 a instep S32 is received, back end server 50 starts to learn various ofvarious pieces of measured data used to detect the designated new action“pulled the gun” through the rewriting operation performed by the userof back end client 70 a (S33). Back end server 50 performs, for example,deep learning using action table Atb1 a recorded on storage 58 aslearning in step S33, and thus learns various pieces of measured dataused to detect the designated new action “pulled the gun”.

In a case where the learning in step S33 is completed, back end server50 updates action table Atb1 b by using results (that is, various piecesof measured data used to detect the designated new action “pulled thegun”) of the learning in step S33 (S34). Back end server 50 transmitsthe results (that is, various pieces of measured data used to detect thedesignated new action “pulled the gun”) of the learning in step S33 towearable camera 10 (S35).

Wearable camera 10 receives the results (that is, various pieces ofmeasured data used to detect the designated new action “pulled the gun”)of the learning transmitted in step S35, and updates action table Atb1recorded on memory 13 or recorder 15 (S36). Consequently, wearablecamera 10 can reflect and record a learning result of measured data inback end server 50 having a higher performance specification than thatof wearable camera 10, and can thus detect an action or a symptom (referto FIG. 15) with high accuracy.

As mentioned above, in the modification example of Exemplary Embodiment1, back end server 50 learns information regarding motion of a policeofficer used to detect a designated new default event in response to arewriting operation on information regarding a default event in actiontable Atb1 a (event table) which is recorded on storage 58 (secondrecorder) and is used to detect a default event. Back end server 50transmits a learning result of the information regarding motion of thepolice officer to wearable camera 10. Wearable camera 10 receives thelearning result of the information regarding motion of the policeofficer transmitted from back end server 50. Wearable camera 10determines whether or not the designated new default event has occurredby using the received learning result of the information regardingmotion of the police officer.

Consequently, wearable camera 10 can reflect and record a learningresult of measured data in back end server 50 having a higherperformance specification than that of wearable camera 10, and can thusdetect an action or a symptom (refer to FIG. 15) with high accuracy.

History of Reaching Exemplary Embodiment 2

In the configuration disclosed in Japanese Patent Unexamined PublicationNo. 2016-122918, it is not taken into consideration that, in a casewhere a user (for example, a police officer) wearing or carrying awearable camera is in an emergency situation in a case field, thewearable camera sends a support request to an investigation headquarterof the case provided in a police department. Regarding the emergencysituation, for example, in a state a police officer is wounded in onehand, and levels a gun with the other hand, the police officer cannotsend a support request via police wireless communication. As mentionedabove, there may be a need for sending a support request to aninvestigation headquarter according to a body posture or a state of apolice officer even in an emergency situation in which it is hard forthe police officer to operate a wearable camera.

Therefore, in Exemplary Embodiment 2, in light of the circumstances, adescription will be made of examples of a wearable camera and aninformation notification method in which, even in a situation in whichit is hard for a user (for example, a police officer) to operate thewearable camera, a notification of a message such as a support requestis sent to the outside (for example, an investigation headquarter) inresponse to a posture or a state of the police officer, and thusrescuing the police officer in early stage is efficiently supported.

Exemplary Embodiment 2

A configuration of a wearable camera system of Exemplary Embodiment 2and an internal configuration of each apparatus forming the wearablecamera system are the same as those in Exemplary Embodiment 1.Therefore, in Exemplary Embodiment 2, a constituent element having thesame content as that of each constituent element forming the wearablecamera system of Exemplary Embodiment 1 is given the same referencenumeral, description thereof will be made briefly or omitted, anddifferent content will be described.

In Exemplary Embodiment 2, an investigation headquarter which is adestination notified of a message by wearable camera 10 in apredetermined case (specifically, refer to step S8B in FIG. 22) is anorganization called an investigation headquarter or a specialinvestigation headquarter provided in police department PD, in a casewhere for example, a special event such as a case or a disaster hasoccurred. In Exemplary Embodiment 2, in a case where wearable camera 10notifies an investigation headquarter of a message, the message isreceived by a data reception device (refer to the following description;for example, back end streaming server 60 or back end server 50)disposed in the investigation headquarter.

A data accumulation device such as back end server 50 or back endstreaming server 60 connected to back end client 70 a is generallydisposed in the investigation headquarter or the special investigationheadquarter. In a case where a message from wearable camera 10 isreceived by the data accumulation device, a police officer who is a userof back end clients 70 a and 70 b recognizes that there is a supportrequest sent from police officer 3 in an emergency situation in a casefield, and reports the content thereof to a superior officer or thelike. Thereafter, under the order of the top (for example, a commandingofficer) of the investigation headquarter or the special investigationheadquarter, judgement to send more police officers to the case field isperformed in order to rescue police officer 3 in an emergency situationin an early stage.

The concept of judgement to send police officers using a message fromwearable camera 10 may be changed as appropriate depending oninvestigation policy or the like of an investigation headquarter or aspecial investigation headquarter in the police, and thus the concept isonly an example. Hereinafter, an investigation headquarter and a specialinvestigation headquarter are unified to an “investigation headquarter”without being particularly differentiated from each other.

FIG. 22 is a flowchart illustrating a detailed example of an operationprocedure of sending a notification to an investigation headquarter onthe basis of detection of a default action in wearable camera 10 ofExemplary Embodiment 2. In description of FIG. 22, the same content asthat of the description of FIG. 6 or 16 will be made briefly or omitted,and different content will be described. FIG. 22 will be describedassuming that the power sources of wearable camera 10 and activity meter200 are in an ON state.

In FIG. 22, in wearable camera 10, after step S5A, action informationgenerator 19D refers to action table Atb1 (refer to FIG. 7), anddetermines an action of police officer 3 by using at least two types ofmeasured data among the five types of measured data (that is, theacceleration data and the inclination data in the three-axis directionsof the orthogonal coordinate system, the sound analysis result data, thevideo analysis result data, and the measured data in activity meter 200)acquired in the respective processes in steps S3 to S5 and S5A (S6A).The processes from step S6A are the same as those in FIG. 6, and thusdescription thereof will be omitted.

Wearable camera 10 determines whether or not there is a default event(for example, an action corresponding to action information defined inaction table Atb1 (refer to FIG. 7)) among behaviors of police officer 3as a result of the determination in step S6A (S7).

In a case where it is determined that there is no default event (forexample, an action corresponding to action information defined in actiontable Atb1 (refer to FIG. 7)) among behaviors of police officer 3 (S7:NO), the process in wearable camera 10 returns to step S2. In otherwords, in this case, wearable camera 10 does not notify theinvestigation headquarter of a message such as a support requestassuming that police officer 3 wearing or carrying wearable camera 10 isnot in an emergency situation in a case field, for example, and performsthe respective processes in step S2 to step S7. On the other hand, in acase where it is determined that there is a default event (for example,an action corresponding to action information defined in action tableAtb1 (refer to FIG. 7)) among behaviors of police officer 3 (S7: YES),wearable camera 10 notifies the investigation headquarter of a messagesuch as a support request assuming that police officer 3 wearing orcarrying wearable camera 10 is in an emergency situation in a casefield, for example (S8B).

In a case where wearable camera 10 notifies the investigationheadquarter (for example, back end streaming server 60 or back endserver 50) of the message, the message may be transmitted according tothe following two transmission methods.

In a first transmission method, in a case where wearable camera 10includes a communicator which can use a cellular network (mobile phonenetwork) such as Long Term Evolution (LTE), wearable camera 10 maytransmit the message to back end streaming server 60 or back end server50 via the communicator by using, for example, an LTE line.Consequently, wearable camera 10 can omit control of communication withsmart phone 40 or wireless LAN access point 45, and can thus directlyand rapidly notify back end streaming server 60 or back end server 50 ofa message.

In a second transmission method, wearable camera 10 may transmit amessage to back end streaming server 60 or back end server 50 via smartphone 40 or wireless LAN access point 45 by using a wireless LAN (WLAN)such as WiFi (registered trademark). Consequently, wearable camera 10can reduce power consumption of wearable camera 10 which is driven withthe battery more than in a case of transmitting a message by using anLTE line. In the second method, a wireless LAN such as WiFi (registeredtrademark) is used between wearable camera 10 and smart phone 40 orwireless LAN access point 45, and a cellular network (mobile phonenetwork) such as an LTE line is used between smart phone 40 or wirelessLAN access point 45 and back end streaming server 60 or back end server50.

FIG. 23 is a flowchart illustrating a detailed example of a datatransmission operation procedure after a notification is sent to theinvestigation headquarter in wearable camera 10 of Exemplary Embodiment2. In description of FIG. 23, the same content as that of thedescription of FIG. 22 will be made briefly or omitted, and differentcontent will be described. FIG. 23 will be described assuming that thepower sources of wearable camera 10 and activity meter 200 are in an ONstate.

In FIG. 23, for example, as described with reference to steps S1 to S5and S9 in FIG. 16, wearable camera 10 acquires the five types ofmeasured data (that is, the acceleration data and the inclination datain the three-axis directions of the orthogonal coordinate system, thesound analysis result data, the video analysis result data, and themeasured data in activity meter 200) (S41). After step S41, as describedwith reference to FIG. 22, in wearable camera 10, the respectiveprocesses are performed in an order of step S6A and step S7.

On the other hand, in a case where it is determined that there is adefault event (for example, an action corresponding to actioninformation defined in action table Atb1 (refer to FIG. 7)) amongbehaviors of police officer 3 (S7: YES), wearable camera 10 notifies(transmits) the investigation headquarter of a message such as a supportrequest assuming that police officer 3 wearing or carrying wearablecamera 10 is in an emergency situation in a case field, for example(S42).

After step S42, wearable camera 10 refers to, for example, the settingfile recorded on memory 13 or recorder 15, and determines whether or nottransmission of a thumbnail image is set (S43). The thumbnail imagefunctions as an evidence image schematically showing a situation of thebehavior (action) of police officer 3 at the detection point in step S7.In a case where it is determined that transmission of a thumbnail imageis not set (S43: NO), the process in wearable camera 10 proceeds to stepS45.

On the other hand, in a case where it is determined that transmission ofa thumbnail image is set (S43: YES), wearable camera 10 generates athumbnail image with a compressed still image format such as JointPhotographic Experts Group (JPEG) by using captured video data (forexample, captured video data with a compressed moving image format suchas Moving Picture Experts Group (MPEG) 4) generated by video/sound datagenerator 19A. Wearable camera 10 transmits data regarding the generatedthumbnail image to the investigation headquarter (for example, back endstreaming server 60 or back end server 50) (S44). Either one of theabove-described two transmission methods is used for the transmission instep S44. After step S44, the process in wearable camera 10 proceeds tostep S45.

Wearable camera 10 refers to, for example, the setting file recorded onmemory 13 or recorder 15, and determines whether or not streaming ofcaptured video data is set (S45). In a case where it is determined thatstreaming of captured video data is not set (S45: NO), the process inwearable camera 10 returns to step S41.

On the other hand, in a case where it is determined that streaming ofcaptured video data is set (S45: YES), wearable camera 10 transmitscaptured video data (for example, captured video data with a compressedmoving image format such as Moving Picture Experts Group (MPEG) 4)generated by video/sound data generator 19A to the investigationheadquarter (for example, back end streaming server 60 or back endserver 50) (S46). Either one of the above-described two transmissionmethods is used for the transmission in step S46. After step S46, theprocess in wearable camera 10 proceeds to step S45.

As mentioned above, in wearable camera system 1000 of ExemplaryEmbodiment 2, wearable camera 10 records captured videos of a subject onthe front side of police officer 3 on recorder 15, and acquiresinformation (for example, acceleration data or inclination data in thethree-axis directions of the orthogonal coordinate system, and dataregarding an activity amount acquired from activity meter 200) regardingmotion of police officer 3. Wearable camera 10 determines whether or notat least one default event (for example, the actions or the symptomsillustrated in FIG. 15) has occurred on the basis of the informationregarding motion of police officer 3 acquired (specifically, measured)during recording of captured videos of the subject. Wearable camera 10notifies (transmits) an investigation headquarter of a message such as asupport request according to determination that at least one defaultevent (for example, the actions illustrated in FIG. 5) has occurredduring recording of captured videos of the subject.

Consequently, for example, assuming that police officer 3 wearing orcarrying wearable camera 10 is in an emergency situation in a casefield, wearable camera 10 can notify the outside (for example, aninvestigation headquarter) of a message such as a support requestaccording to a body posture or a state of police officer 3 even in asituation it is hard for police officer 3 to operate wearable camera 10.Therefore, wearable camera 10 can effectively support the investigationheadquarter in rescuing police officer 3 in an early stage.

Wearable camera 10 of the present exemplary embodiment may notify aninvestigation headquarter of a message such as a support request, maygenerate event list information (for example, action index AL1) in whicha detection time point of the default event is correlated withinformation regarding the default event, and may record the event listinformation on recorder 15 in correlation with the captured videos ofthe subject, in combination with above Exemplary Embodiment 1.

Wearable camera 10 may further record information indicating that anotification of a message such as a support request has been sent to aninvestigation headquarter and information regarding a notification timepoint on recorder 15 in correlation with each other. Consequently,wearable camera 10 can reliably store history that a message such as asupport request has transmitted to an investigation headquarter in anemergency situation of police officer 3 in a case field, and can thuscontribute to posterior examination of a behavior or a situation ofpolice officer 3 during handling of a case.

In a case where wearable camera 10 notifies an investigation headquarterof a message such as a support request, a thumbnail image based on acaptured video obtained at the time of transmitting the message may betransmitted to the investigation headquarter according to the content ofthe setting file recorded on memory 13 or recorder 15. Consequently,wearable camera 10 can provide the thumbnail image from which anemergency situation of police officer 3 can be roughly understood to aninvestigation headquarter, and can thus contribute to a prompt judgementof the investigation headquarter.

In a case where wearable camera 10 notifies an investigation headquarterof a message such as a support request, wearable camera 10 may subjectcaptured videos obtained at the time of transmission of the message tostreaming transmission to the investigation headquarter according to thecontent of the setting file recorded on memory 13 or recorder 15.Consequently, wearable camera 10 can provide captured video data fromwhich an emergency situation of police officer 3 can be understood indetail to an investigation headquarter, and can thus contribute to aprompt and accurate judgement of the investigation headquarter.

History of Reaching Exemplary Embodiment 3

As a current business practice in the police, the following work isperformed as follows. For example, if a case occurs, assuming that acriminal of the case makes a preliminary examination of a case field, aplurality of police officers watch and check the content of capturedvideos obtained and recorded by all of cameras within a few kilometersof the surroundings of the case field for a predetermined time beforethe case occurred, and narrow down captured videos related to the case.The number of captured videos of which the content is to be checked maybe enormous depending on property or a scale of a case, and thus thereis a problem in which a large amount of work man-hours is required untila plurality of police officers complete checking of the content.

However, in the configuration disclosed in Japanese Patent UnexaminedPublication No. 2016-122918, it is not taken into consideration that atechnical countermeasure for solving the problem is taken. In otherwords, in the related art such as Japanese Patent Unexamined PublicationNo. 2016-122918, video analysis for narrowing down captured videosrelated to a case cannot be performed by using captured videos obtainedand recorded for a predetermined time before the case occurred.

Therefore, in Exemplary Embodiment 3, in light of the circumstances, adescription will be made of examples of a server apparatus, a wearablecamera, and a video analysis method in which video analysis fornarrowing down captured videos related to an event such as a case isperformed by using a recorded captured video, and thus the time andeffort required to retrieve a target captured video are reduced.

Exemplary Embodiment 3

FIG. 24 is a schematic diagram illustrating a configuration example ofwearable camera system 1000A of Exemplary Embodiment 3. Wearable camerasystem 1000A of Exemplary Embodiment 3 has the same configuration asthat of wearable camera system 1000 (refer to FIG. 1) of ExemplaryEmbodiment 1, and is configured to further include a plurality ofmonitoring cameras CC1 to CCn (where n is a natural number of 2 orgreater). FIG. 24 illustrates wearable camera 10, monitoring cameras CC1to CCn, back end server 50, and back end clients 70 related todescription of Exemplary Embodiment 3 as representatives compared withwearable camera system 1000 in FIG. 1, but is not intended to excludeconfigurations of other respective apparatuses illustrated in FIG. 1.FIG. 24 illustrates only a single wearable camera 10, but the number ofwearable cameras 10 forming wearable camera system 1000A is not limitedto one, and may be plural.

An internal configuration of each apparatus forming wearable camerasystem 1000A of Exemplary Embodiment 3 is the same as that in ExemplaryEmbodiment 1. Therefore, in Exemplary Embodiment 3, a constituentelement having the same content as that of each constituent elementforming the wearable camera system of Exemplary Embodiment 1 is giventhe same reference numeral, description thereof will be made briefly oromitted, and different content will be described.

Internal configurations of respective monitoring cameras CC1 to CCn mayor may not be the same as each other. For better understanding of thefollowing description, intersection configurations of respectivemonitoring cameras CC1 to CCn are assumed to be the same as each other.

Each of monitoring cameras CC1 to CCn images subjects present in alocation (for example, on a street, in front of a station, at astorefront, or in a store) where the monitoring camera is installed.Each of monitoring cameras CC1 to CCn writes (records) captured videodata to a recorder (for example, a recorder corresponding to recorder 15of wearable camera 10) built into the monitoring camera. Monitoringcameras CC1 to CCn transmit (upload) the captured video data to back endserver 50 or back end streaming server 60 in police department PD at apredetermined timing (for example, in a periodic manner at apredetermined time interval, or a time point at which a request fromback end server 50 or back end streaming server 60 in police departmentPD is received; the same applies hereinafter).

Wearable camera 10 similarly also transmits (uploads) the captured videodata to back end server 50 or back end streaming server 60 in policedepartment PD at a predetermined timing (for example, in a periodicmanner at a predetermined time interval, or a time point at which arequest from back end server 50 or back end streaming server 60 inpolice department PD is received).

Back end client 70 corresponds to back end clients 70 a and 70 b in FIG.1, and is formed by using, for example, a personal computer (PC) used bypolice officer 3. Back end client 70 transmits an instruction forretrieving a captured video which is a retrieval operation target toback end server 50 in response to a retrieval operation (which will bedescribed later) performed by police officer 3 who is a user. Back endclient 70 displays captured video data as an extraction result(retrieval result) transmitted from back end server 50 on a monitor (notillustrated), and reproduces and outputs selected captured video data ina case where an instruction for reproduction is given through anoperation performed by police officer 3.

Back end server 50 (server apparatus) receives captured video datatransmitted (uploaded) from each of monitoring cameras CC1 to CCn, andperforms a video analysis process for extracting meta-information (whichwill be described later). The video analysis process in back end server50 is performed according to a well-known technique using, for example,captured video data CPD1. Back end server 50 generates videoaccumulation data DAT1 in which meta-information MTF1 extracted throughthe video analysis process is correlated with captured video data CPD1,and records video accumulation data DAT1 on storage 58 (refer to FIG.11) and thus stores video accumulation data DAT1 (refer to FIG. 25).Back end server 50 searches storage 58 so as to retrieve and extractcorresponding captured video data according to a retrieval instructiontransmitted from back end client 70. Back end server 50 transmitscaptured video data as an extraction result (retrieval result) to backend client 70.

FIG. 25 is a diagram illustrating a configuration example of videoaccumulation data DAT1 recorded on back end server 50 of ExemplaryEmbodiment 3. Video accumulation data DAT1 includes captured video dataCPD1 which is uploaded from any camera (that is, any of monitoringcameras CC1 to CCn and wearable camera 10) and received, andmeta-information MTF1 obtained through the video analysis process inback end server 50.

Here, meta-information MTF1 will be described. Meta-information MTF1 isused for back end server 50 to retrieve and extract a retrieval targetcaptured video on the basis of a retrieval instruction from back endclient 70. Meta-information MTF1 is attribute information used to tracktraces of a suspect or a criminal in order to extract captured videodata in which the suspect or the criminal was reflected before a caseoccurred or when the case occurred.

Meta-information MTF1 is, for example, a color of a vehicle reflected incaptured video data CPD1, a vehicle number reflected in captured videodata CPD1, or a manufacturer, a model name, and a model year of avehicle reflected in captured video data CPD1. On the basis ofmeta-information MTF1, back end server 50 can specifically specify, forexample, a vehicle used by a suspect or a criminal when the suspect orthe criminal made preliminary examination before a case occurred. Backend server 50 can specifically specify, for example, a vehicle used inescape of a suspect or a criminal when a case occurred.

Meta-information MTF1 is, for example, whether or not an article (forexample, a vehicle) reflected in captured video data CPD1 is damaged,and a damaged part.

On the basis of meta-information MTF1, for example, in a case where anarticle reflected in captured video data CPD1 is related to a case, backend server 50 can specify a damaged part of the article from residuesreflected in captured video data CPD1. If a damaged part (for example, acertain component of a vehicle) can be specified by back end server 50,police officer 3 who is a user of back end client 70 can specificallyspecify, for example, a vehicle used when a suspect or a criminalescaped in a hurry.

Meta-information MTF1 is, for example, a traveling speed of a vehiclereflected in captured video data CPD1, or whether or not the travelingspeed is higher than a normal traveling speed (for example, the legallimit) in an area including a location where any camera corresponding tocaptured video data CPD1 is installed. For example, in a case where avehicle reflected captured video data CPD1 is related to a case, thereis a high probability that a suspect or a criminal might drive thevehicle at a speed higher than a normal traveling speed for escape. Onthe basis of meta-information MTF1, back end server 50 can specificallyspecify that a vehicle traveled at a speed higher than a normaltraveling speed might be used by a suspect or a criminal.

FIG. 26 is a sequence diagram illustrating a detailed example of ananalysis operation procedure for captured video data transmitted fromwearable camera 10 or a monitoring camera in back end server 50 ofExemplary Embodiment 3. For better understanding of description of FIG.26, a single monitoring camera and a single wearable camera areillustrated, but the same procedure also applies in a case where aplurality of wearable cameras and monitoring cameras are provided. InFIG. 26, the monitoring camera is indicated by a closed-circuittelevision (CCTV), and monitoring camera CC1 will be described as anexample. In FIG. 26, monitoring camera CC1 records captured video dataof subjects present in a location (for example, on a street, in front ofa station, at a storefront, or in a store) where the monitoring camerais installed, on a recorder (not illustrated) built into monitoringcamera CC1 (S51 a). Monitoring camera CC1 transmits (uploads) thecaptured video data to back end server 50 or back end streaming server60 in police department PD at a predetermined timing (refer to the abovedescription) (S52 a).

Wearable camera 10 records captured video data of subjects present in alocation (for example, a case field or the periphery of the case field)where a user (for example, police officer 3) wearing or holding thewearable camera is present, on recorder 15 built into wearable camera 10(S51 b). Wearable camera 10 transmits (uploads) the captured video datato back end server 50 or back end streaming server 60 in policedepartment PD at a predetermined timing (refer to the above description)(S52 b).

Back end server 50 receives the captured video data transmitted frommonitoring camera CC1 and wearable camera 10 in steps S51 b and S52 b.Back end server 50 performs a video analysis process on the basis of thecaptured video data, and determines whether or not there ismeta-information of a captured video (S53).

Back end server 50 determines whether or not meta-information can beextracted as a result of the video analysis process in step S53 (S54).In a case where it is determined that meta-information cannot beextracted (that is, there is no meta-information) (S54: NO), the processin step S53 is repeatedly performed until meta-information can beextracted.

In a case where it is determined that meta-information can be extracted(S54: YES), back end server 50 records captured video data CPD1 which isa target of the video analysis process and extracted meta-informationMTF1 on storage 58 in correlation with each other (S55).

Here, for example, a case is assumed in which a professional in policedepartment PD who wants to retrieve captured video data related to acase operates back end client 70. Police officer 3 who has patrolled acase field may operate back end client 70 instead of the professional.

Back end client 70 detects that a retrieval operation for captured videodata related to a case has been input by the professional (refer to theabove description) or police officer 3 who is a user (S56). In theretrieval operation, it is assumed that, regarding meta-information,“red” is specifically input as a “color of a vehicle”, and “ABC-1234” isspecifically input as a “vehicle number”. Back end client 70 transmits aretrieval instruction for a captured video which is a retrievaloperation target to back end server 50 according to input of theretrieval operation (S57). The retrieval instruction includes themeta-information (that is, “red” as a “color of a vehicle”, and“ABC-1234” as a “vehicle number”) which is input during the retrievaloperation.

In a case where the retrieval instruction transmitted in step S57 isreceived, back end server 50 retrieves and extracts captured video datamatching a retrieval condition on the basis of the retrieval instructionand the meta-information recorded on storage 58 (S58). Back end server50 returns the captured video data extracted in step S58 to back endclient 70 (S59).

Back end client 70 displays the captured video data as an extractionresult (retrieval result) transmitted from back end server 50 on amonitor (not illustrated), and reproduces and outputs selected capturedvideo data in a case where an instruction for reproduction is giventhrough an operation performed by the professional (refer to the abovedescription) or police officer 3 who is a user (S60).

As mentioned above, in wearable camera system 1000A of ExemplaryEmbodiment 3, monitoring cameras CC1 to CCn or wearable camera 10transmits (uploads) captured video data obtained through imaging thereinto back end server 50 at a predetermined timing. Back end server 50 hasbeen described as an example of a server apparatus which is an uploaddestination, but back end streaming server 60 may be an uploaddestination. In this case, captured video data which is uploaded istransmitted from back end streaming server 60 to back end server 50.Back end server 50 performs a video analysis process on the uploadedcaptured video data, so as to extract meta-information regarding thecaptured video data, and accumulates video accumulation data DAT1 inwhich captured video data CPD1 is correlated with meta-information MTF1in storage 58.

Consequently, back end server 50 can perform video analysis fornarrowing down captured video data related to an event such as a case byusing captured video data recorded by each of monitoring cameras CC1 toCCn and wearable camera 10, and can thus accumulate meta-informationwhich is helpful in verification of relevance between a video reflectedin the captured video data and the case along with the captured videodata. Therefore, back end server 50 can reduce the time and effortrequired to retrieve a target captured video.

Back end server 50 retrieves captured video data includingmeta-information from storage 58 in response to a retrieval operationincluding the meta-information which is input by a user of back endclient 70, and returns the extracted captured video data to back endclient 70. Consequently, back end server 50 can easily and efficientlyretrieve captured video data related to a case desired to be retrievedby a user (for example, the professional (refer to the abovedescription) or police officer 3) of back end client 70, and can thuscontribute to reducing work man-hours of the user required to retrievecaptured video data related to the case.

History of Reaching Exemplary Embodiment 4

The content of Exemplary Embodiment 4 relates to an informationprocessing apparatus and an information processing method of displayinga desired captured video by using information regarding a behavior of auser in captured videos.

In the related art, a recording device which performs imaging or soundcollecting in a state of being attached to a user's body has beenproposed (for example, refer to Japanese Patent Unexamined PublicationNo. 2007-49592). The recording device is wearable, and an imaging visualfield thereof is set to substantially match a visual field of a user.The recording device registers position information, movement speedchange information, and biological signal change information everypredetermined time corresponding to a period from the start of recordingof video recording data or sound recording data to the end thereof in adatabase. The recording device compares the content of the database witha condition for adding a bookmark, a time to add a bookmark to the videorecording data or sound recording data is specified, and the bookmark isadded at the specified time, so that management during reproduction isperformed.

However, in Japanese Patent Unexamined Publication No. 2007-49592, in acase where a plurality of users (for example, police officers) arerelated to a certain incident (for example, a case) occurred already,and a video which may serve as an evidence in the case or a videoshowing a situation at the time of the case is captured by a recordingdevice worn or carried by each user, it is not taken into considerationthat a video at a point at which a behavior gaining attention wasperformed is efficiently retrieved. Therefore, in a case where acaptured video from each viewpoint of a plurality of police officers atthe point at which the behavior getting attention in the case wasperformed is requested, in order to accurately extract the capturedvideo, a lot of manual laborious work (for example, work of viewing andchecking each captured video with the naked eyes) is required. Thisincreases the number of work processes required to extract a necessarycaptured video, and thus there is a problem in that convenience duringextraction is not sufficient.

Therefore, in Exemplary Embodiment 4, in light of the circumstances ofthe related art, a description will be made of examples of aninformation processing apparatus and an information processing method inwhich, in a case where a plurality of users are related to a certainincident occurred already, a captured video at a point at which abehavior gaining attention was performed is accurately extracted amongcaptured videos in wearable cameras worn or carried by the respectiveusers, and improvement of convenience during extraction of a capturedvideo desired by a user is supported.

Exemplary Embodiment 4

A configuration of a wearable camera system of Exemplary Embodiment 4and an internal configuration of each apparatus forming wearable camerasystem are the same as those in Exemplary Embodiment 1. Therefore, inExemplary Embodiment 4, a constituent element having the same content asthat of each constituent element forming the wearable camera system ofExemplary Embodiment 1 is given the same reference numeral, descriptionthereof will be made briefly or omitted, and different content will bedescribed.

First, with reference to FIG. 27, a description will be made of aninternal configuration of back end client 70 (which is the same as backend clients 70 a and 70 b illustrated in FIG. 1) as an example of aninformation processing apparatus related to Exemplary Embodiment 4. Theinformation processing apparatus related to Exemplary Embodiment 4 maybe back end server 50 illustrated in FIGS. 1 and 11.

FIG. 27 is a block diagram illustrating a detailed example of aninternal configuration of the back end client of Exemplary Embodiment 4.Back end client 70 includes CPU 151, I/O controller 152, communicator153, memory 154, input 155, display 156, and speaker 159.

CPU 151 performs a control process of integrating operations of therespective constituent elements of back end client 70 as a whole, aprocess of transmitting and receiving data to and from the otherrespective constituent elements, a data calculation (computation)process, and a data storage process. CPU 151 is operated according to aprogram and data stored in memory 154.

I/O controller 152 performs control on input and output of data betweenCPU 151 and the respective constituent elements (for example,communicator 153, input 155, and display 156) of back end client 70, andrelays data from CPU 151 and data to CPU 151. I/O controller 152 may beformed integrally with CPU 151.

Communicator 153 performs wired communication with wearable camera 10connected to a wired LAN in police department PD. Communicator 153 mayperform wired or wireless communication with, for example, in-carrecorder 33, in-car PC 32, smart phone 40, wearable camera 10 which canbe worn or held by police officer 3, or back end server 50.

Memory 154 is formed by using, for example, a RAM, a ROM, and anonvolatile or volatile semiconductor memory, functions as a work memoryduring an operation of CPU 151, and stores a predetermined program anddata for operating CPU 151. Memory 154 (third recorder) records capturedvideos of a subject transmitted from wearable camera 10 and action indexAL1 in correlation with each other in the same manner as storage 58 ofback end server 50. In a case where an information processing apparatusrelated to Exemplary Embodiment 4 is back end server 50, storage 58(third recorder) records captured videos of a subject transmitted fromwearable camera 10 and action index AL1 in correlation with each otherin the same manner as storage 58 of back end server 50.

Input 155 is a user interface (UI) which receives an input operationperformed by a user (for example, police officer 3 or theabove-described professional) of back end client 70 in police departmentPD, and notifies CPU 151 of the input operation via I/O controller 152,and is a pointing device such as a mouse or a keyboard. Input 155 may beformed by using a touch panel or a touch pad which is disposed tocorrespond to, for example, a screen of display 156, and in which anoperation can be performed with the finger of a person in charge or astylus pen.

Display 156 (monitor) is formed by using, for example, a liquid crystaldisplay (LCD) or an organic EL display, and displays various pieces ofinformation. For example, in a case where captured videos obtained orrecorded by wearable camera 10 are input according to an input operationperformed by a user, display 156 displays the captured videos on ascreen under an instruction of CPU 151. For example, in a case wherecaptured videos recorded by in-car cameras 31 are input according to aninput operation performed by a user, display 156 displays the capturedvideos on a screen under an instruction of CPU 151.

For example, in a case where sounds collected by wearable camera 10 areinput according to an input operation performed by a user, speaker 159outputs the collected sounds under an instruction of CPU 151.

Next, a description will be made of an operation example after actionindex AL1 and captured videos generated by different wearable cameras 10are recorded on back end client 70 of police department PD for backup.Here, a case is assumed in which, for example, in a case where aplurality of police officers are related to (participate in) a certainincident (for example, a case) occurred already, a captured video at apoint at which a behavior getting attention was performed by a user (forexample, police officer 3) as a party related to the case is retrievedand watched among captured videos in wearable cameras 10 worn or carriedby the respective police officers. A plurality of captured videos at thepoint at which the behavior getting attention was performed areextracted, and thus it is possible to perform multilateral situationjudgement based on viewpoints of a plurality of police officers.However, an operation example is not limited to the above-describedassumed example.

FIG. 28 is a diagram illustrating an example of retrieval result screenWD3 displaying an entry field for a captured video retrieval conditionand a retrieval result. Retrieval result screen WD3 illustrated in FIG.28 is an example of a screen displayed on display 156 as a processingresult in a dedicated application (for example, a retrieval application(specifically, CPU 151) for a captured video) which is installed inadvance to be executable in back end client 70. In a case where aninformation processing apparatus related to Exemplary Embodiment 4 isback end server 50, the retrieval application is formed of, for example,CPU 51, and, hereinafter, CPU 151 may be replaced with CPU 51. In thefollowing description, police officer 3 described in each of theabove-described exemplary embodiments will be referred to as policeofficer A. Police officer 3 may not be a party related to a case, and,in this case, police officer 3 and police officer A may be differentpersons. A description will be made assuming that police officer A is aparty related to a case.

Retrieval result screen WD3 illustrated in FIG. 28 includes date andtime entry field IP1, retrieval word entry field IP3, retrieval buttonSC1, and retrieval result list OP2 indicating a list of captured videos.The date and time which is a retrieval target is entered into date andtime entry field IP1 through an operation performed by, for example,police officer 3 as a party related to a case in the retrievalapplication for a captured video. Various retrieval conditions forextracting a retrieval target captured video are entered into retrievalword entry field IP3. In the example illustrated in FIG. 28, the “casenumber 20170620-0023” is entered. In other words, a captured video (inother words, a captured video regarding a twenty-third case occurred onJun. 20, 2017) having an attribute of the “case number 20170620-0023” asmeta-information MTF1 (for example, refer to FIG. 25) of the capturedvideo is retrieved.

For example, in a state in which retrieval result list OP2 is notdisplayed (in other words, a state before retrieval) on retrieval resultscreen WD3 illustrated in FIG. 28, if retrieval button SC1 is pressedaccording to entry of a retrieval condition from police officer 3, theretrieval application (specifically, CPU 151 as a retrieval processor)for a captured video retrieves one or more captured videos havingmetadata of the “case number 20170620-0023” by referring to memory 154on which action index AL1 and captured video data are recorded incorrelation with each other. The retrieval application (specifically,CPU 151 as a display controller) for a captured video displays retrievalresult screen WD3 (refer to FIG. 28) including a list of a plurality ofcaptured videos extracted through the retrieval and multi-simultaneousreproduction display button MPB1 (which will be described later) ondisplay 156.

For example, in retrieval result list OP2, extracted records RC11, RC12,RC13, RC14, and RC15 of five captured videos are displayed, andmulti-simultaneous reproduction display button MPB1 (predetermined icon)is displayed to be selectable. For example, in FIG. 28,multi-simultaneous reproduction display button MPB1 is provided as abutton for displaying a screen on which the respective extracted fivecaptured videos can be reproduced simultaneously in a single screen(so-called multi-simultaneous reproduction). In each of records RC11 toRC15, a checkbox for designating whether or not a target of themulti-simultaneous reproduction is set, a file name of captured videodata, a thumbnail image, the date and time (not illustrated in FIG. 28),information regarding an imaging person (that is, a police officerwearing or holding wearable camera 10), and reproduction button RP1 forthe captured video data are correlated with each other. The thumbnailimage is an image (for example, a still image, or a moving image in ananimation form) generated on the basis of a captured video at adetection point at which an action (refer to FIG. 15) was detected amongcaptured videos corresponding to a file name.

According to record RC11 of retrieval result list OP2, with respect topolice officer A, it can be seen that a file name of captured video datarelated to the case with the “case number 20170620-0023” is “A.mp4”, andthumbnail image SM31 at a point at which an action of police officer Awas detected among captured videos is displayed.

Similarly, according to record RC12 of retrieval result list OP2, withrespect to police officer B, it can be seen that a file name of capturedvideo data related to the case with the “case number 20170620-0023” is“B.mp4”, and thumbnail image SM32 at a point at which an action ofpolice officer B was detected among captured videos is displayed.

Similarly, according to record RC13 of retrieval result list OP2, withrespect to police officer C, it can be seen that a file name of capturedvideo data related to the case with the “case number 20170620-0023” is“C.mp4”, and thumbnail image SM33 at a point at which an action ofpolice officer C was detected among captured videos is displayed.

Similarly, according to record RC14 of retrieval result list OP2, withrespect to police officer D, it can be seen that a file name of capturedvideo data related to the case with the “case number 20170620-0023” is“D.mp4”, and thumbnail image SM34 at a point at which an action ofpolice officer D was detected among captured videos is displayed.

Similarly, according to record RC15 of retrieval result list OP2, withrespect to police officer E, it can be seen that a file name of capturedvideo data related to the case with the “case number 20170620-0023” is“E.mp4”, and thumbnail image SM35 at a point at which an action ofpolice officer E was detected among captured videos is displayed. Here,it is assumed that, for example, all of the checkboxes for records

RC11 and RC15 are selected, and then multi-simultaneous reproductiondisplay button MPB1 is pressed (an operation of selecting apredetermined icon) through an operation performed by a user (forexample, police officer 3 as a party who has participated in the “casenumber 20170620-0023”). In this case, the retrieval application(specifically, CPU 151 as a display controller) for a captured videodisplays a video reproduction screen (for example, multi-simultaneousreproduction screen WD4) including a captured video correlated with eachwearable camera 10 and event list information (for example, action indexAL1) corresponding to the captured video, on display 156 (refer to FIG.29).

FIG. 29 is a diagram illustrating an example of multi-simultaneousreproduction screen WD4 based on pressing of multi-simultaneousreproduction display button MPB1 in retrieval result screen WD3 in FIG.28. Multi-simultaneous reproduction screen WD4 (video reproductionscreen) illustrated in FIG. 29 is an example of a screen displayed ondisplay 156 as a processing result in the retrieval application(specifically, CPU 151) for a captured video which is installed inadvance to be executable in back end client 70.

Multi-simultaneous reproduction screen WD4 illustrated in FIG. 29displays that, for example, captured videos MV1 a, MV1 b, MV1 c, MV1 dand MV1 e in respective wearable cameras 10 and correlation tables DT11,DT12, DT13, DT14 and DT15 are associated with respective wearablecameras 10 of five police officers. The five police officers are, forexample, A with the identification number “HP2345”, B with theidentification number “HP3456”, C with the identification number“HP2374”, D with the identification number “HP2534”, and E with theidentification number “HP2464”.

A reproduction button (for example, reproduction button MRP3), a pausebutton (for example, pause button TH11), a seek bar (for example, seekbar SKB2), a marker (for example, marker MK2 a), and detection markers(for example, detection markers SP11, SP12, SP13, SP14 and SP15) aredisplayed in correlation with a display region of each other betweeneach of captured videos MV1 a to MV1 e and each of correlation tablesDT11 to DT15. The seek bar (for example, seek bar SKB2) indicates areproducible period (that is, a recording period) of each of capturedvideos MV1 a to MV1 e.

The marker (for example, marker MK2 a) indicates a reproduction timepoint (that is, a reproduction position) of a captured video. Thedetection markers (for example, detection markers SP11 to SP15) indicatedetection timings of an action or a symptom detected during recording ofeach captured video.

In FIG. 29, for simplification of description, in correlation tablesDT11 to DT15, in a case where an action or a symptom of each policeofficer was actually detected, a specific action or symptom is writtenin the action field, and, in a case where an action or a symptom was notdetected, “. . . ” is written for convenience. In correlation tableDT11, a total of five actions or symptoms of police officer A wereactually detected, but, in order to avoid complexity of the drawing, atotal of four actions or symptoms are illustrated, and a reproductiontime field and an action field for the fifth action or symptom are notillustrated. Therefore, as illustrated in correlation tables DT11 toDT15, with respect to the case with the “case number 20170620-0023”, itcan be seen that a total of five actions or symptoms were detected forpolice officer A, and a total of two actions or symptoms were detectedfor each of police officers B, C, D and E.

A recording starting time (recording starting time point) of eachcorresponding captured video is displayed on the left side of eachdisplay region of correlation tables DT11 to DT15 in FIG. 29. In otherwords, it can be seen that wearable camera 10 of police officer Astarted recording at “03:03:04 p.m. on Jun. 20, 2017”.

Similarly, it can be seen that wearable camera 10 of police officer Bstarted recording at “03:03:24 p.m. on Jun. 20, 2017”. Similarly, it canbe seen that wearable camera 10 of police officer C started recording at“03:03:22 p.m. on Jun. 20, 2017”. Similarly, it can be seen thatwearable camera 10 of police officer D started recording at “03:03:25p.m. on Jun. 20, 2017”. Similarly, it can be seen that wearable camera10 of police officer E started recording at “03:03:21 p.m. on Jun. 20,2017”.

Individual report creation buttons VDR1, VDR2, VDR3, VDR4 and VDRS forgenerating case basis event history lists (which will be describedlater) which are required for respective police officers A to E toindividually create case reports are displayed on the left sides of thedisplay regions of correlation tables DT11 to DT15 in

FIG. 29. Details of individual report creation buttons VDR1 to VDRS willbe described later.

Multi-simultaneous reproduction screen WD4 displays, for example, actionmap MP11 (event map information) indicating position information of whena captured video is recorded by wearable camera 10 of each of the fivepolice officers. Specifically, pieces of position information P1A, P1B,P1C, P1D and P1LE of respective police officers A, B, C, D and E aredisplayed in action map MP11 illustrated in FIG. 29. For example, on themulti simultaneous reproduction screen WD 4, it is triggered that, amongthe five police officers, police officer A recorded a captured videorelated to the case. This is clear from the fact that a recordingstarting time of a captured video in wearable camera 10 of policeofficer A is earliest. It is illustrated that police officer A sent asupport request to other police officers B, C, D and E, and other policeofficers B, C, D and E started recording in respective wearable cameras10 according to the support request from police officer A.Multi-simultaneous reproduction screen WD4 displays, for example,multi-simultaneous reproduction button MLS1 (simultaneous reproductionicon) for instructing captured videos in respective wearable cameras 10of the five police officers to be reproduced simultaneously. In a casewhere it is detected that multi-simultaneous reproduction button MLS1has been pressed through an operation performed by, for example, policeofficer 3, the retrieval application (specifically, CPU 151 as a displaycontroller) for a captured video performs a simultaneous reproductionprocess on respective captured videos MV1 a, MV1 b, MV1 c, MV and MV1 efrom the same reproduction time (a reproduction starting point) anddisplays the captured videos on multi-simultaneous reproduction screenWD4. 30-second simultaneous fast reversing button ABF30, simultaneouspause button TH21, 30-second simultaneous fast forwarding button AAF30are displayed on the lower part of the display region ofmulti-simultaneous reproduction button MLS1 in FIG. 29. Here, “30seconds” of 30-second simultaneous fast reversing button ABF30 or30-second simultaneous fast forwarding button AAF30 is only an example,and a time is not limited to 30 seconds. 30-second simultaneous fastreversing button ABF30 is used to adjust simultaneous fast reversing ofreproduction times (reproduction starting points) of five respectivecaptured videos MV1 a, MV1 b, MV1 c, MV1 d and MV1 e inmulti-simultaneous reproduction screen WD4 in FIG. 29 by 30 seconds.Simultaneous pause button TH21 is used to simultaneously pausereproduction of five respective captured videos MV1 a, MV1 b, MV1 c, MV1d and MV1 e in multi-simultaneous reproduction screen WD4 in FIG. 29.30-second simultaneous fast forwarding button AAF30 is used to adjustsimultaneous fast forwarding of reproduction times (reproductionstarting points) of five respective captured videos MV1 a, MV1 b, MV1 c,MV and MV1 e in multi-simultaneous reproduction screen WD4 in FIG. 29 by30 seconds.

Multi-report button MLR1 is displayed on the right part of the displayregion of multi-simultaneous reproduction button MLS1 in FIG. 29.Multi-report button MLR1 (entire history output icon) is used togenerate a case basis event history list (which will be described later)of two or more police officers (for example, police officers A and B)selected (refer to FIG. 34) by a user (for example, police officer 3)through merging. Details of multi-report button MLR1 will be describedlater.

Here, it is assumed that a user (for example, police officer 3) performsan operation using input 155, and thus a cursor (not illustrated) isdisposed on the display region of the record of the fourth row ofcorrelation table DT11 correlated with wearable camera 10 of policeofficer A on multi-simultaneous reproduction screen WD4 illustrated inFIG. 29. At this point, the record of the fourth row is not selected. Inthis case, the retrieval application (specifically, CPU 151) for acaptured video displays the record of the fourth row on which the cursoris disposed to be able to be identified more than other records ofcorrelation tables DT12, DT13, DT14 and DT15. For example, the record ofthe fourth row is displayed to be temporarily selected within dottedframe SLC1. In other words, it is assumed that, among detected actionsof police officer A (that is, the user), the user (for example, policeofficer 3) temporarily selects the action “fell down” detected at thereproduction time “03:20” of captured video MV1 a as an action which theuser is concerned about (that is, which the user is to pay attentionto).

FIG. 30 is a diagram illustrating another example of multi-simultaneousreproduction screen WD4. Multi-simultaneous reproduction screen WD4(video reproduction screen) illustrated in FIG. 30 is a screen displayedon display 156 in a case where the record of the fourth row ofcorrelation table DT11 correlated with wearable camera 10 of policeofficer A, temporarily selected within dotted frame SLC1 in FIG. 29, issubjected to a formal selection operation through an operation performedby the user (for example, police officer 3) by using input 155. Indescription of FIG. 30, a constituent element having the same content asthat in FIG. 29 is given the same reference numeral, description thereofwill be made briefly or omitted, and different content will bedescribed.

In a case where the record of the fourth row of correlation table DT11is subjected to the formal selection operation, the retrievalapplication (specifically, CPU 151) for a captured video displays therecord in a predetermined color (for example, yellow) from dotted frameSLC1. A state of being subjected to the formal selection state isindicated by yellow marker SLC2. The retrieval application(specifically, CPU 151) for a captured video performs a process ofadjusting reproduction times of respective captured videos MV1 a, MV1 b,MV1 c, MV1 d and MV1 e to the reproduction time (specifically, “03:20:15p.m.”) of the record which is a selection operation target according tothe formal selection operation. In FIG. 30, the markers (for example,markers MK2 a, MK2 b, MK2 c, MK2 d and MK2 e) on the seek barsrespectively corresponding to respective captured videos MV1 a, MV1 b,MV1 c, MV1 d and MV1 e are jumped to the position of the reproductiontime “03:20:15 p.m.” from the points (that is, recording starting pointsof the respective captured videos) illustrated in FIG. 29 and aredisplayed. Consequently, times displayed on the lower part of thedisplay regions of the identification numbers of the respective policeofficers in FIG. 30 are simultaneously set to the reproduction time(specifically, “03:20:15 p.m.”) of the record of the fourth row ofcorrelation table DT11 subjected to the formal selection operation.

In a case where the record of the fourth row of correlation table DT11is subjected to the formal selection operation, retrieval application(specifically, CPU 151) for a captured video displays updated positioninformation of each wearable camera 10 in action map MP12 (event mapinformation) at the reproduction time (specifically, “03:20:15 p.m.”) ofthe record which is a selection operation target. In FIG. 30, it can beseen that pieces of position information P2A, P2B, P2C, P2D and P2E arechanged (moved) of police officers A, B, C, D and E compared with actionmap MP11 illustrated in FIG. 29.

FIG. 31 is a diagram illustrating an example of an output video based ona predetermined format. The retrieval application (specifically, CPU151) for a captured video generates, for example, a data file of anoutput video based on a predetermined format to be submitted to aninstitution such as a court or a public prosecutor's office according toan operation performed by a user (for example, police officer 3). In theexample illustrated in FIG. 31, output video OPT1 includes respectivecaptured videos MV1 a, MV1 b, MV1 c, MV1 d and MV1 e at the point atwhich the record of the fourth row of correlation table DT11 wassubjected to the formal selection operation, information regarding thereproduction time thereof (specifically, “03:20:15 p.m. on Jun. 29,2017”), and action map MP12 at the reproduction time (specifically,“03:20:15 p.m. on Jun. 29, 2017”). According to multi-simultaneousreproduction screen WD4 or output video OPT1 illustrated in FIG. 30, ina case where a plurality of parties (for example, police officers) arerelated to a single incident (for example, a case), it is possible toobtain a captured video from which peripheral situations of a case fieldcan be accurately understood in a multilateral manner.

FIG. 32 is a flowchart illustrating a detailed example of a displayoperation procedure corresponding to a captured video retrievalinstruction in back end client 70 of Exemplary Embodiment 4. Indescription of FIG. 32, a case is exemplified in which theabove-described retrieval application for a captured video is installedto be executable in back end client 70, but, as described above, theapplication may be installed to be executable in back end server 50. Inthis case, in description of FIG. 32, each process is CPU 51 of back endserver 50 as described above.

In FIG. 32, CPU 151 of back end client 70 acquires, for example, a casenumber retrieval instruction as a result of a user (for example, policeofficer 3) performing an operation on a screen of the retrievalapplication for a captured video (S61). As the case number retrievalinstruction, for example, the “case number 20170620-0023” is assumed tobe entered.

CPU 151 displays retrieval result screen WD3 (refer to FIG. 28) forvideos captured by a plurality of police officers, corresponding to thesame case number acquired in step S61, on display 156 (S62).

Here, CPU 151 determines whether or not multi-simultaneous reproductiondisplay button MPB1 has been pressed according to an operation performedby the user (for example, police officer 3) (S63). In a case wheremulti-simultaneous reproduction display button MPB1 has been pressed(S63: YES), CPU 151 displays multi-simultaneous reproduction screen WD4(refer to FIG. 29) on display 156 (S64). In a case wheremulti-simultaneous reproduction display button MPB1 has not been pressed(S63: NO), the process in step S63 is repeatedly performed untilmulti-simultaneous reproduction display button MPB1 is pressed.

Here, CPU 151 determines whether or not the cursor (not illustrated) hasbeen moved to an action or a symptom on any correlation table accordingto an operation performed by the user (for example, police officer 3)(S65). In a case where the cursor has been moved to an action or asymptom on any correlation table (S65: YES), CPU 151 displays the actionor the symptom which is a movement destination to be able to beidentified by attaching dotted frame SLC1 thereto. After step S66, in acase where the action or the symptom is subjected to a formal selectionoperation (S67: YES), CPU 151 displays the selected action or system ina color, displays a marker (for example, MK2 a) jumped to a detectiontime point thereof, and further similarly displays markers (for example,MK2 b, MK2 c, MK2 d, and MK2 e) of other captured videos jumped to thesame detection time point (S68).

On the other hand, in a case where the action or the symptom is notsubjected to a formal selection operation (S67: NO), or in a case wherethe cursor has not been moved to any action or symptom (S65: NO), therespective processes in steps S65 to S67 are repeatedly performed untilany action or symptom is subjected to a formal selection operation.

Here, CPU 151 determines whether or not multi-simultaneous reproductionbutton MLS1 has been pressed according to an operation performed by theuser (for example, police officer 3) (S69). In a case wheremulti-simultaneous reproduction button MLS1 has been pressed (S69: YES),CPU 151 performs a process of simultaneously reproducing all capturedvideos displayed on multi-simultaneous reproduction screen WD4 with thedetection time point of the action or the symptom subjected to theformal selection operation in step S67 in multi-simultaneousreproduction screen WD4 (refer to FIG. 30) (S70). In a case wheremulti-simultaneous reproduction button MLS1 has not been pressed (S69:NO), the process in step S69 is repeatedly performed untilmulti-simultaneous reproduction display button MPB1 is pressed.

As mentioned above, in Exemplary Embodiment 4, back end client 70records captured videos in wearable cameras 10 respectively worn orcarried by a plurality of users (for example, police officers), andaction index AL1 (event list information) including respective detectiontime points of a plurality of types of actions or symptoms (defaultevents) detected during recording of the captured videos and informationregarding each action or symptom (event) on memory 154 (third recorder)in correlation with wearable cameras 10. Back end client 70 retrieves acaptured video of an incident (for example, a case) gaining attentionfrom captured videos recorded on memory 154 according to entry of aretrieval condition, and displays retrieval result screen WD3 includinga list of a plurality of captured videos extracted through the retrievaland multi-simultaneous reproduction display button MPB1 (predeterminedicon) on display 156 (monitor). Back end client 70 displaysmulti-simultaneous reproduction screen WD4 (video reproduction screen)including a captured video correlated with each wearable camera 10 andaction index AL1 corresponding to the captured video on display 156according to an operation of selecting multi-simultaneous reproductiondisplay button MPB1.

Consequently, in a case where a plurality of police officers are relatedto a certain incident occurred already, back end client 70 canaccurately extract a captured video at a point at which a behaviorgaining attention was performed is accurately extracted among capturedvideos in wearable cameras worn or carried by the respective policeofficers, and can thus to support improvement of convenience duringextraction of a captured video desired by a user.

Back end client 70 displays all captured videos on multi-simultaneousreproduction screen WD4 switched to a captured video at a detection timepoint of an action or a symptom (selected event) based on a selectionoperation according to an operation of selecting the action or thesymptom (event) included in any correlation table (event listinformation) of multi-simultaneous reproduction screen WD4.Consequently, in a case where a user (for example, police officer 3) ofback end client 70 finds an action or a symptom which the user isconcerned about (which the user is to pay attention to) from eachcorrelation table (event list information) displayed onmulti-simultaneous reproduction screen WD4, the user can view a list ofcaptured videos at a destination time point of the action or the symptomin multilateral visual fields, and can thus efficiently grasp orsummarize situations of a case or the like, by performing an operationof selecting the action or the symptom.

Back end client 70 displays multi-simultaneous reproduction button MLS1(simultaneous reproduction icon) for simultaneously reproducing allcaptured videos of multi-simultaneous reproduction screen WD4 onmulti-simultaneous reproduction screen WD4, and simultaneouslyreproduces and displays captured videos at a detection time point of aselected action or symptom according to a selection operation onmulti-simultaneous reproduction button MLS1. Consequently, a user (forexample, police officer 3) of back end client 70 can understand thespecific content of captured videos after a detection time point of anaction or a system which the user is concerned about (which the user isto pay attention to) from a plurality of captured videos in detail.

On the basis of a selection operation on any captured video ofmulti-simultaneous reproduction screen WD4, back end client 70 displays30-second fast reversing icon VBF30 (first icon) for displaying thecaptured video (selected captured video) based on the selectionoperation switched to a captured video at a time point going back by apredetermined period (for example, 30 seconds), and 30-second fastforwarding icon VAF30 (second icon) for displaying the captured video(selected captured video) switched to a captured video at a time pointat which a predetermined period (for example, 30 seconds) elapses, to besuperimposed on the captured video (selected captured video) (refer toFIG. 30). In a case where back end client 70 detects pressing of30-second fast reversing icon VBF30 or 30-second fast forwarding iconVAF30, and then detects selection of reproduction button VRP1, back endclient 70 performs a process of reproducing the captured video (selectedcaptured video). Consequently, a user (for example, police officer 3) ofback end client 70 can understand the specific content of capturedvideos before or after a detection time point of an action or a systemwhich the user is concerned about (which the user is to pay attentionto) individually in detail, for example, in a single captured video (forexample, captured video MV1 a).

Back end client 70 displays an action or a symptom (selected event)based on a selection operation of a user (for example, police officer 3)to be able to be identified compared with other actions or symptoms(default events) which are not targets of the selection operation (referto FIG. 30). Consequently, a user (for example, police officer 3) ofback end client 70 can easily check an action or a system which the useris concerned about (which the user is to pay attention to).

The correlation table (event list information) may further includeposition information of wearable camera 10 in the same manner as actionindex AL1. In this case, back end client 70 displays action map MP11(event map information) displaying respective pieces of positioninformation of a plurality of wearable cameras 10 at a detection timepoint of an action or a symptom (selected event) based on a selectionoperation of a user (for example, police officer 3) onmulti-simultaneous reproduction screen WD4. Consequently, a user (forexample, police officer 3) of back end client 70 can geographicallyunderstand position information of the user or other police officers ata detection time point of an action or a system which the user isconcerned about (which the user is to pay attention to), and can thusremember the situation at that time, and this can contribute tosupporting creation of a case report or the like.

Modification Example of Exemplary Embodiment 4

In a modification example of Exemplary Embodiment 4, a description willbe made of an example of an information processing apparatus (forexample, back end client 70) which supports creation of a time-seriesprogress report for actions or symptoms to be attached to a case reportin a case where a party (for example, police officer 3) related to acertain incident (for example, a case) is required to create the casereport as business thereof. However, in the same manner as in ExemplaryEmbodiment 4, an information processing apparatus related to themodification example of Exemplary Embodiment 4 may be back end client70, and may be back end server 50. In the following description, a casetype of the case with the “case number 20170620-0023” in ExemplaryEmbodiment 4 is assumed to be a “firearm” which will be described later.

FIG. 33A is a diagram illustrating a first example of case basis eventhistory list ALLT1 corresponding to case basis unique event list CStb1in the modification example of Exemplary Embodiment 4. FIG. 33B is adiagram illustrating a second example of case basis event history listALLT2 corresponding to case basis unique event list CStb2 in themodification example of Exemplary Embodiment 4.

Case basis unique event list CStb1 is, for example, a table defining alist of actions or systems which are more likely to be performed by apolice officer in a case in which the police officer used a gun with acase type as a “firearm”, and is registered in, for example, memory 154in advance. Case basis unique event list CStb1 includes actions orsystems such as “dangerous falling”, “dashed”, “hit”, “pulled the gun”,“stop order”, “leveled the gun”, and “shot the gun”.

For example, in a case where pressing of the individual report creationbutton (for example, individual report creation button VDR1) in FIG. 29or 30 is detected, CPU 151 of back end client 70 refers to case basisunique event list CStb1 in memory 154, and generates and outputs casebasis event history list ALLT1 in which the various actions or symptomsdefined in case basis unique event list CStb1 are correlated withdetection time points thereof. An output destination of case basis eventhistory list ALLT1 may be, for example, display 156, and may be memory154 as a data storage destination.

There may be an action or a system which is registered in case basisunique event list CStb1 but was not detected in wearable camera 10. Theexample in FIG. 33A shows that the actions “dangerous falling” and “hit”were not detected in wearable camera 10. Police officer 3 can rememberthe actions “dangerous falling” and “hit”, and can complementarilyreport time points at which the actions occurred.

Case basis unique event list CStb2 is, for example, a table defining alist of actions or systems which are more likely to be performed by apolice officer in a case of having cracked down on drunken driving ordriving under the use of drugs with a case type as “DUI”, and isregistered in, for example, memory 154 in advance. Case basis uniqueevent list CStb2 includes, for example, actions or symptoms such as“started recording”, “got off the car”, “started walking”, “startedinterview”, and “got on the car”.

In a case where pressing of the individual report creation button of themulti-simultaneous reproduction screen (refer to FIG. 29 or 30)regarding the case with “DUI” as a case type is detected, CPU 151 ofback end client 70 refers to case basis unique event list CStb2 inmemory 154, and generates and outputs case basis event history listALLT2 in which the various actions or symptoms defined in case basisunique event list CStb2 are correlated with detection time pointsthereof. An output destination of case basis event history list ALLT2may be, for example, display 156, and may be memory 154 as a datastorage destination.

As mentioned above, in the modification example of Exemplary Embodiment4, back end client 70 further records the case basis unique event list(unique event list) in which a plurality of actions or symptoms uniquelydetected for each incident (for example, a case) are registered inadvance for each incident (for example, a case). Back end client 70displays the individual report creation button (individual historyoutput icon) in correlation with each captured video ofmulti-simultaneous reproduction screen WD4, and outputs case basis eventhistory list ALLT1 including an action or a system detected from acaptured video (selected captured video) based on a selection operationand a detection time point on the basis of the case basis unique eventlist corresponding to an incident in multi-simultaneous reproductionscreen WD4 according to the selection operation on any individual reportcreation button. Consequently, in a case where police officer 3 as aparty directly related to a case is required to create a case report ofthe case associated with business thereof, police officer 3 can easilycreate a time-series progress report for actions or symptoms to beattached to the case report.

In the modification example of Exemplary Embodiment 4, in a case where aplurality of police officers are related to the same case, back endclient 70 may generate merged history of actions or symptoms detected inthe plurality of police officers.

FIG. 34 is a diagram illustrating another example of retrieval resultscreen WD3 displaying an entry field for a captured video retrievalcondition and a retrieval result. FIG. 35 is a diagram illustrating afirst example of multi-simultaneous reproduction screen WD4 based onpressing of multi-simultaneous reproduction display button MPB1 inretrieval result screen WD3 in FIG. 34.

In description of FIG. 34, a constituent element having the same contentas that in FIG. 28 is given the same reference numeral, descriptionthereof will be made briefly or omitted, and different content will bedescribed. In FIG. 34, two records RC11 and RC12 are selected in orderto generate a case basis event history list by merging actions orsymptoms of, for example, police officers A and B with each other.

In back end client 70, in a case where pressing of multi-simultaneousreproduction display button MPB1 in FIG. 34 is detected, the retrievalapplication for a captured video displays multi-simultaneousreproduction screen WD5 illustrated in FIG. 35 on display 156. Inmulti-simultaneous reproduction screen WD5 illustrated in FIG. 35,unlike multi-simultaneous reproduction screen WD4 illustrated in FIG.29, captured videos MV1 a and MV1 b in wearable cameras 10 correspondingto records RC11 and RC12 selected by a user (for example, police officer3), correlation tables DT11 and DT12, and the like are displayed. Indescription of FIG. 35, a constituent element having the same content asthat in FIG. 29 is given the same reference numeral, description thereofwill be made briefly or omitted, and different content will bedescribed.

FIG. 36A is a diagram illustrating an example of case basis eventhistory list ALLT3 of police officer A with the identification number“HP2345”. FIG. 36B is a diagram illustrating an example of case basisevent history list ALLT4 of police officer B with the identificationnumber “HP3456”.

Case basis event history list ALLT3 illustrated in FIG. 36A is generatedby the retrieval application (specifically, CPU 151) for a capturedvideo by using case basis unique event list CStb1 (refer to FIG. 33A) onthe basis of pressing of individual report creation button VDR1 inmulti-simultaneous reproduction screen WD5 illustrated in FIG. 35.Similarly, case basis event history list ALLT4 illustrated in FIG. 36Bis generated by the retrieval application for a captured video by usingcase basis unique event list CStb1 (refer to FIG. 33A) on the basis ofpressing of individual report creation button VDR2 in multi-simultaneousreproduction screen WD5 illustrated in FIG. 35.

FIG. 37A is a diagram illustrating an example of case basis eventhistory list ALLT5 into which case basis event history lists ALLT3 andALLT4 of police officers A and B with the identification numbers“HP2345” and “HP3456” are merged.

As mentioned above, back end client 70 further records the unique eventlist in which a plurality of actions or symptoms detected in an incident(for example, a case) are registered in advance for each incident, onmemory 154. Back end client 70 displays the individual report creationbutton (individual history output icon) in correlation with eachcaptured video of multi-simultaneous reproduction screen WD5, andgenerates and outputs the case basis event history list including anaction or a system detected from a captured video (selected capturedvideo) based on a selection operation and a detection time point on thebasis of the case basis unique event list corresponding to an incidentin multi-simultaneous reproduction screen WD5 according to the selectionoperation on any individual report creation button. An outputdestination may be, for example, display 156, and may be memory 154 as adata storage destination.

As mentioned above, the retrieval application (specifically, CPU 151)for a captured video generates the case basis event history list byusing case basis unique event list CStb1 (refer to FIG. 33A) on thebasis of pressing of multi-report button MLR1 in multi-simultaneousreproduction screen WD5 illustrated in FIG. 35. Specifically, in a casewhere pressing of multi-report button MLR1 in multi-simultaneousreproduction screen WD5 illustrated in FIG. 35 is detected, CPU 151generates case basis event history lists ALLT3 and ALLT4 of policeofficers A and B illustrated in FIGS. 36A and 36B, and merges the liststogether. Consequently, police officer 3 as a party directly related toa case can easily create a case report representing a time-seriesprogress report for actions or symptoms detected in each police officerin a case where there are a plurality of police officers in the caseassociated with business thereof.

FIG. 37B is a diagram illustrating an example of action map MP12 inwhich information regarding positions where actions in case basis eventhistory lists ALLT3 and ALLT4 in FIGS. 36A and 36B are detected isdisplayed to be superimposed on map data.

The correlation table (event list information) in the multi-simultaneousreproduction screen may further include position information of wearablecamera 10 in the same manner as action index AL1. The retrievalapplication (specifically, CPU 151) for a captured video superimposesposition information at a detection time point of each action or symptomon the map data so as to generate and output action map MP12 illustratedin FIG. 37 by using case basis event history list ALLT5 illustrated inFIG. 37A according to an operation of a user (for example, policeofficer 3). In other words, back end client 70 outputs action map MP12(event map information) indicating position information of each of aplurality of wearable cameras 10 at determination time points of allevents in a plurality of selected captured videos (captured videoscorresponding to records RC11 and RC12). Consequently, back end client70 can geographically and intuitively make it easy to understand interimprogress or interim behaviors until two police officers A and B go tocase field CSC1.

In Exemplary Embodiment 4 and the modification example of ExemplaryEmbodiment 4, back end client 70 may perform a process in which a user(for example, police officer 3) enters a retrieval condition (forexample, the date and time or a case number), and back end server 50 mayperform each process of retrieval based on the entered retrievalcondition and display of retrieval result screen WD3, so that therespective processes are shared by back end client 70 and back endserver 50. Of course, the opposite case may also be employed. In otherwords, back end server 50 may perform a process in which a user (forexample, police officer 3) enters a retrieval condition (for example,the date and time or a case number), and back end client 70 may performeach process of retrieval based on the entered retrieval condition anddisplay of retrieval result screen WD3. In this case, in retrievalresult screen WD3 for captured videos extracted through the retrievalprocess in back end server 50 or back end client 70, display ofmulti-simultaneous reproduction screens WD4 and WD5 based on pressing ofmulti-simultaneous reproduction display button MPB1, and a process ofreproducing various captured videos after the display or a process ofdisplaying various pieces of information or data is performed in backend client 70 or back end server 50. In other words, retrieval of acaptured video is performed in back end client 70 including memory 154on which a captured video of a subject and action index AL1 are recordedin correlation with each other, or back end server 50 including storage58 on which a captured video of a subject and action index AL1 arerecorded in correlation with each other. Consequently, a retrievalprocess with a great processing load is distributed to anotherapparatus, and thus it is possible to reduce a processing load on backend client 70 or back end server 50 which does not perform a retrievalprocess.

As mentioned above, various exemplary embodiments have been describedwith reference to the drawings, but it is needless to say that thepresent disclosure is not limited to the examples. It is clear that aperson skilled in the art can conceive of various alterations ormodifications within the category recited in the claims, and it isunderstood that they are naturally included in the technical scope ofthe present disclosure. The respective constituent elements in theexemplary embodiments may be arbitrarily combined within the scopewithout departing from the scope of the invention.

The present disclosure is useful as a wearable camera, a wearable camerasystem, and an information recording method, in which, even if a userdoes not independently reproduce or watch a recorded captured video,each of various behaviors of the user performed in a time series isdetermined from a captured video recorded by the wearable camera, and isrecorded as information, and business of the user is efficientlysupported.

What is claimed is:
 1. A wearable device, comprising: a video camera that captures video of a subject on a front side of a user of the wearable device and records the captured video on a recorder; a motion sensor that acquires information regarding motion of the user in association with the captured video, the motion sensor being operative to detect at least one default event; and a controller that: determines, based on the information regarding motion of the user acquired by the sensor, whether the at least one default event has occurred during capture of the video of the subject; in response to determining that the at least one default event has occurred during the recording of the captured video of the subject, generates event list information in which a detection time of the at least one default event is associated with information regarding the at least one default event; and records, on the recorder, the event list information in association with the captured video of the subject.
 2. The wearable device of claim 1, wherein the controller generates a thumbnail image corresponding to the detection time of the at least one default event by using the captured video of the subject, and records the event list information including the generated thumbnail image on the recorder.
 3. The wearable device of claim 1, further comprising: a position information acquirer that acquires position information of the wearable camera, and wherein the controller acquires position information of the wearable device corresponding to the detection time of the at least one default event, further generates event map information in which the acquired position information is superimposed on map data, and records the event map information on the recorder.
 4. The wearable device of claim 1, further comprising: a sound collector that collects sounds around the user, wherein the controller determines whether the at least one default event has occurred based on the information regarding motion of the user acquired by the motion sensor and sounds collected by the sound collector during recording of the captured video of the subject.
 5. The wearable device of claim 1, further comprising: a communicator that performs communication with an external sensor acquiring information regarding an activity amount of the user, wherein the controller determines whether the at least one default event has occurred based on the information regarding motion of the user acquired by the motion sensor and information regarding an activity amount of the user received from the external sensor during recording of the captured video of the subject.
 6. A wearable device system comprising: a wearable camera that is able to be worn or carried by a user; and a server that is communicably connected to the wearable camera, wherein the wearable camera: captures a video of a subject on a front side of the user and records the captured video on a recorder, acquires information regarding motion of the user during recording of the captured video of the subject, and transmits the acquired information regarding motion of the user to the server, wherein the server: receives the information regarding motion of the user transmitted from the wearable camera, determines whether at least one default event has occurred based on the received information regarding motion of the user, and transmits an instruction for generating event list information in which a detection time of the least one default event is associated with information regarding the at least one default event to the wearable camera according to determination that the at least one default event has occurred, and wherein the wearable camera: receives the instruction for generating the event list information transmitted from the server, and generates the event list information in response to the received instruction for generating the event list information, and records the generated event list information on the recorder in association with the captured video of the subject.
 7. The wearable camera system of claim 6, wherein the wearable camera: transmits the captured video of the subject recorded on the recorder and the event list information to the server in association with each other, and wherein the server: receives the captured video of the subject and the event list information transmitted from the wearable camera, and records the captured video of the subject and the event list information on a second recorder in association with each other.
 8. The wearable camera system of claim 7, wherein the server: extracts at least one captured video in which the at least one default event which is a target of a retrieval operation is detected from the second recorder in response to the retrieval operation on the information regarding the at least one default event, and displays a retrieval result screen on which a thumbnail image corresponding to the extracted captured video is displayed, on a display.
 9. The wearable camera system of claim 8, wherein the server: displays the retrieval result screen including a reproduction button for the at least one extracted captured video on the display, and displays a watching screen for the captured video which is a target of a designation operation on the display in response to the designation operation on the reproduction button.
 10. The wearable camera system of claim 9, wherein the server: displays the watching screen including a second reproduction button for a captured video corresponding to a detection time of at least one event detected in the captured video which is a target of the designation operation on the display.
 11. An information processing apparatus comprising: a recorder on which captured videos in wearable cameras respectively worn or carried by a plurality of users, and event list information including each detection time of a plurality of types of default events detected during recording of the captured videos and information regarding each of the events are recorded in association with the wearable cameras; a retrieval processor that retrieves captured videos of an incident gaining attention from the captured videos recorded on the recorder in response to entry of a retrieval condition; and a display controller that displays a retrieval result screen including a list of a plurality of the captured videos extracted through the retrieval and a predetermined icon on a monitor, wherein the display controller displays a video reproduction screen including the captured videos associated with each of the wearable cameras and the event list information corresponding to the captured videos on the monitor in response to a selection operation on the predetermined icon.
 12. The information processing apparatus of claim 11, wherein the display controller displays all of the captured videos in the video reproduction screen switched to a captured video at a detection time of a selected event based on a selection operation in response to the selection operation on the event included in any event list information in the video reproduction screen.
 13. The information processing apparatus of claim 12, wherein the display controller displays a simultaneous reproduction icon for simultaneously reproducing all of the captured videos in the video reproduction screen on the video reproduction screen, and simultaneously reproduces and displays captured videos at the detection time of the selected event in response to a selection operation on the simultaneous reproduction icon.
 14. The information processing apparatus of claim 11, wherein, in response to the selection operation on any of the captured videos in the video reproduction screen, the display controller displays a first icon for displaying a selected captured video based on the selection operation switched to a captured video at a time point going back by a predetermined period, and a second icon for displaying the selected captured video switched to a captured video at a time point at which a predetermined period elapses, to be superimposed on the selected captured video.
 15. The information processing apparatus of claim 12, wherein the display controller displays the selected event to be able to be identified compared with the other default events which are not targets of the selection operation.
 16. The information processing apparatus of claim 12, wherein the event list information further includes position information of the wearable camera, and wherein the display controller displays event map information indicating position information of each of a plurality of wearable cameras at the detection time of the selected event on the video reproduction screen.
 17. The information processing apparatus of claim 11, wherein a unique event list in which a plurality of the events detected in the incident are registered in advance for each incident is further recorded on the recorder, and wherein the display controller displays an individual history output icon in association with each of the captured videos in the video reproduction screen, and outputs an event history list including an event detected in a selected captured video based on a selection operation and a detection time of the event on the basis of the unique event list corresponding to an incident in the video reproduction screen in response to the selection operation on the individual history output icon.
 18. The information processing apparatus of claim 11, wherein a unique event list in which a plurality of the events detected in the incident are registered in advance for each incident is further recorded on the recorder, and wherein the display controller displays an entire history output icon on the video reproduction screen, and outputs an event history list including all events detected in a plurality of selected captured videos based on a selection operation and detection time points of the events on the basis of the unique event list corresponding to an incident in the video reproduction screen in response to the selection operation on the entire history output icon.
 19. The information processing apparatus of claim 18, wherein the event list information further includes position information of the wearable camera, and wherein the display controller outputs event map information indicating position information of each of a plurality of wearable cameras at detection time points of all events in the plurality of selected captured videos. 